VCBM 19: Eurographics Workshop on Visual Computing for Biology and Medicine

Permanent URI for this collection

Brno, Czech Republic, September 4-6, 2019
Visual Computing for MRI-based Data
SpectraMosaic: An Exploratory Tool for the Interactive Visual Analysis of Magnetic Resonance Spectroscopy Data
Laura Garrison, Jakub Vašíček, Renate Grüner, Noeska N. Smit, and Stefan Bruckner
Multiparametric Magnetic Resonance Image Synthesis using Generative Adversarial Networks
Christoph Haarburger, Nicolas Horst, Daniel Truhn, Mirjam Broeckmann, Simone Schrading, Christiane Kuhl, and Dorit Merhof
Colonic Content Assessment From MRI Imaging Using a Semi-automatic Approach
Victor Ceballos, Eva Monclús, Pere-Pau Vázquez, Álvaro Bendezú, Marianela Mego, Xavier Merino, Fernando Azpiroz, and Isabel Navazo
A Web-based Application for the Visual Exploration of Colon Morphology Data
Jan Males, Eva Monclús, Jose Díaz, and Pere-Pau Vázquez
Interactive Formation of Statistical Hypotheses in Diffusion Tensor Imaging
Amin Abbasloo, Vitalis Wiens, Tobias Schmidt-Wilcke, Pia Sundgren, Reinhard Klein, and Thomas Schultz
Semantic Segmentation of Brain Tumors in MRI Data Without any Labels
Leon Weninger, Imke Krauhausen, and Dorit Merhof
Visual Analytics in Medicine and Biology
Feasibility Study For Automatic Bird Tracking and Visualization from Time-Dependent Marine Radar Imagery
Florian Ganglberger and Katja Bühler
A Visual Environment for Hypothesis Formation and Reasoning in Studies with fMRI and Multivariate Clinical Data
Daniel Jönsson, Albin Bergström, Camilla Forsell, Rozalyn Simon, Maria Engström, Anders Ynnerman, and Ingrid Hotz
Pelvis Runner: Visualizing Pelvic Organ Variability in a Cohort of Radiotherapy Patients
Nicolas Grossmann, Oscar Casares-Magaz, Ludvig Paul Muren, Vitali Moiseenko, John P. Einck, Eduard Gröller, and Renata Georgia Raidou
preha: Establishing Precision Rehabilitation with Visual Analytics
Georg Bernold, Kresimir Matkovic, Eduard Gröller, and Renata Georgia Raidou
A Visual Analytics Approach for Patient Stratification and Biomarker Discovery
Shiva Alemzadeh, Florian Kromp, Bernhard Preim, Sabine Taschner-Mandl, and Katja Bühler
MedUse: A Visual Analysis Tool for Medication Use Data in the ABCD Study
Hauke Bartsch, Laura Garrison, Stefan Bruckner, Ariel Wang, Susan F. Tapert, and Renate Grüner
Molecular Visualization (I)
Interactive Exploded Views for Molecular Structures
Maximilian Sbardellati, Haichao Miao, Hsiang-Yun Wu, Eduard Gröller, Ivan Barisic, and Ivan Viola
DockVis: Visual Analysis of Molecular Docking Data
Katarina Furmanová, Barbora Kozlíková, Vojtech Vonásek, and Jan Byška
Digital Pathology, Surgery, and Anatomical Education
Layer-Aware iOCT Volume Rendering for Retinal Surgery
Jakob Weiss, Ulrich Eck, Muhamad Ali Nasseri, Mathias Maier, Abouzar Eslami, and Nassir Navab
Visual Analytics in Digital Pathology: Challenges and Opportunities
Alberto Corvò, Michel A. Westenberg, Reinhold Wimberger-Friedl, Stephan Fromme, Michel M. R. Peeters, Marc A. van Driel, and Jarke J. van Wijk
Animation, Tracking, and Simulations
Medical Animations: A Survey and a Research Agenda
Bernhard Preim and Monique Meuschke
Using Position-Based Dynamics for Simulating the Mitral Valve in a Decision Support System
Lars Walczak, Joachim Georgii, Lennart Tautz, Mathias Neugebauer, Isaac Wamala, Simon Sündermann, Volkmar Falk, and Anja Hennemuth
InkVis: A High-Particle-Count Approach for Visualization of Phase-Constrast Magnetic Resonance Imaging Data
Niels H. L. C. de Hoon, Kai Lawonn, Andrei C. Jalba, Elmar Eisemann, and Anna Vilanova
Robustness Evaluation of CFD Simulations to Mesh Deformation
Alexander Scheid-Rehder, Kai Lawonn, and Monique Meuschke
The Vitruvian Baby: Interactive Reformation of Fetal Ultrasound Data to a T-Position
Eric Mörth, Renata Georgia Raidou, Ivan Viola, and Noeska N. Smit
HIFUpm: a Visual Environment to Plan and Monitor High Intensity Focused Ultrasound Treatments
Daniela Modena, Davide Bassano, Aaldert Elevelt, Marco Baragona, Peter A. J. Hilbers, and Michel A. Westenberg
Molecular Visualization (II)
Hybrid Visualization of Protein-Lipid and Protein-Protein Interaction
Naif Alharbi, Michael Krone, Matthieu Chavent, and Robert S. Laramee
Molecular Sombreros: Abstract Visualization of Binding Sites within Proteins
Karsten Schatz, Michael Krone, Tabea L. Bauer, Valerio Ferrario, Jürgen Pleiss, and Thomas Ertl
Interactive CPU-based Ray Tracing of Solvent Excluded Surfaces
Tobias Rau, Sebastian Zahn, Michael Krone, Guido Reina, and Thomas Ertl
Blood Flow and Vascular Visualization
Evolutionary Pathlines for Blood Flow Exploration in Cerebral Aneurysms
Benjamin Behrendt, Wito Engelke, Philipp Berg, Oliver Beuing, Bernhard Preim, Ingrid Hotz, and Sylvia Saalfeld
Distance Field Visualization and 2D Abstraction of Vessel Tree Structures with on-the-fly Parameterization
Nils Lichtenberg, Bastian Krayer, Christian Hansen, Stefan Müller, and Kai Lawonn

BibTeX (VCBM 19: Eurographics Workshop on Visual Computing for Biology and Medicine)
@inproceedings{
10.2312:vcbm.20191225,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
SpectraMosaic: An Exploratory Tool for the Interactive Visual Analysis of Magnetic Resonance Spectroscopy Data}},
author = {
Garrison, Laura
and
Vašíček, Jakub
and
Grüner, Renate
and
Smit, Noeska N.
and
Bruckner, Stefan
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191225}
}
@inproceedings{
10.2312:vcbm.20191227,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Colonic Content Assessment from MRI Imaging Using a Semi-automatic Approach}},
author = {
Ceballos, Victor
and
Monclús, Eva
and
Vázquez, Pere-Pau
and
Bendezú, Álvaro
and
Mego, Marianela
and
Merino, Xavier
and
Azpiroz, Fernando
and
Navazo, Isabel
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191227}
}
@inproceedings{
10.2312:vcbm.20191226,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Multiparametric Magnetic Resonance Image Synthesis using Generative Adversarial Networks}},
author = {
Haarburger, Christoph
and
Horst, Nicolas
and
Truhn, Daniel
and
Broeckmann, Mirjam
and
Schrading, Simone
and
Kuhl, Christiane
and
Merhof, Dorit
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191226}
}
@inproceedings{
10.2312:vcbm.20191228,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
A Web-based Application for the Visual Exploration of Colon Morphology Data}},
author = {
Males, Jan
and
Monclús, Eva
and
Díaz, Jose
and
Vázquez, Pere-Pau
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191228}
}
@inproceedings{
10.2312:vcbm.20191229,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Interactive Formation of Statistical Hypotheses in Diffusion Tensor Imaging}},
author = {
Abbasloo, Amin
and
Wiens, Vitalis
and
Schmidt-Wilcke, Tobias
and
Sundgren, Pia
and
Klein, Reinhard
and
Schultz, Thomas
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191229}
}
@inproceedings{
10.2312:vcbm.20191230,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Semantic Segmentation of Brain Tumors in MRI Data Without any Labels}},
author = {
Weninger, Leon
and
Krauhausen, Imke
and
Merhof, Dorit
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191230}
}
@inproceedings{
10.2312:vcbm.20191231,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Feasibility Study For Automatic Bird Tracking and Visualization from Time-Dependent Marine Radar Imagery}},
author = {
Ganglberger, Florian
and
Bühler, Katja
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191231}
}
@inproceedings{
10.2312:vcbm.20191232,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
A Visual Environment for Hypothesis Formation and Reasoning in Studies with fMRI and Multivariate Clinical Data}},
author = {
Jönsson, Daniel
and
Bergström, Albin
and
Forsell, Camilla
and
Simon, Rozalyn
and
Engström, Maria
and
Ynnerman, Anders
and
Hotz, Ingrid
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191232}
}
@inproceedings{
10.2312:vcbm.20191233,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Pelvis Runner: Visualizing Pelvic Organ Variability in a Cohort of Radiotherapy Patients}},
author = {
Grossmann, Nicolas
and
Casares-Magaz, Oscar
and
Muren, Ludvig Paul
and
Moiseenko, Vitali
and
Einck, John P.
and
Gröller, Eduard
and
Raidou, Renata Georgia
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191233}
}
@inproceedings{
10.2312:vcbm.20191234,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
preha: Establishing Precision Rehabilitation with Visual Analytics}},
author = {
Bernold, Georg
and
Matkovic, Kresimir
and
Gröller, Eduard
and
Raidou, Renata Georgia
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191234}
}
@inproceedings{
10.2312:vcbm.20191236,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
MedUse: A Visual Analysis Tool for Medication Use Data in the ABCD Study}},
author = {
Bartsch, Hauke
and
Garrison, Laura
and
Bruckner, Stefan
and
Wang, Ariel
and
Tapert, Susan F.
and
Grüner, Renate
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191236}
}
@inproceedings{
10.2312:vcbm.20191235,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
A Visual Analytics Approach for Patient Stratification and Biomarker Discovery}},
author = {
Alemzadeh, Shiva
and
Kromp, Florian
and
Preim, Bernhard
and
Taschner-Mandl, Sabine
and
Bühler, Katja
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191235}
}
@inproceedings{
10.2312:vcbm.20191238,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
DockVis: Visual Analysis of Molecular Docking Data}},
author = {
Furmanová, Katarína
and
Kozlíková, Barbora
and
Vonásek, Vojtěch
and
Byška, Jan
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191238}
}
@inproceedings{
10.2312:vcbm.20191237,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Interactive Exploded Views for Molecular Structures}},
author = {
Sbardellati, Maximilian
and
Miao, Haichao
and
WU, Hsiang-Yun
and
Groeller, Eduard
and
Barisic, Ivan
and
Viola, Ivan
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191237}
}
@inproceedings{
10.2312:vcbm.20191239,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Layer-Aware iOCT Volume Rendering for Retinal Surgery}},
author = {
Weiss, Jakob
and
Eck, Ulrich
and
Nasseri, Muhamad Ali
and
Maier, Mathias
and
Eslami, Abouzar
and
Navab, Nassir
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191239}
}
@inproceedings{
10.2312:vcbm.20191241,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Medical Animations: A Survey and a Research Agenda}},
author = {
Preim, Bernhard
and
Meuschke, Monique
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191241}
}
@inproceedings{
10.2312:vcbm.20191242,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Using Position-Based Dynamics for Simulating the Mitral Valve in a Decision Support System}},
author = {
Walczak, Lars
and
Georgii, Joachim
and
Tautz, Lennart
and
Neugebauer, Mathias
and
Wamala, Isaac
and
Sündermann, Simon
and
Falk, Volkmar
and
Hennemuth, Anja
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191242}
}
@inproceedings{
10.2312:vcbm.20191240,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Visual Analytics in Digital Pathology: Challenges and Opportunities}},
author = {
Corvò, Alberto
and
Westenberg, Michel A.
and
Wimberger-Friedl, Reinhold
and
Fromme, Stephan
and
Peeters, Michel M. R.
and
Driel, Marc A. van
and
Wijk, Jarke J. van
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191240}
}
@inproceedings{
10.2312:vcbm.20191243,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
InkVis: A High-Particle-Count Approach for Visualization of Phase-Contrast Magnetic Resonance Imaging Data}},
author = {
de Hoon, Niels
and
Lawonn, Kai
and
Jalba, Andrei
and
Eisemann, Elmar
and
Vilanova, Anna
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191243}
}
@inproceedings{
10.2312:vcbm.20191244,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Robustness Evaluation of CFD Simulations to Mesh Deformation}},
author = {
Scheid-Rehder, Alexander
and
Lawonn, Kai
and
Meuschke, Monique
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191244}
}
@inproceedings{
10.2312:vcbm.20191246,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
HIFUpm: a Visual Environment to Plan and Monitor High Intensity Focused Ultrasound Treatments}},
author = {
Modena, Daniela
and
Bassano, Davide
and
Elevelt, Aaldert
and
Baragona, Marco
and
Hilbers, Peter A. J.
and
Westenberg, Michel A.
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191246}
}
@inproceedings{
10.2312:vcbm.20191245,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
The Vitruvian Baby: Interactive Reformation of Fetal Ultrasound Data to a T-Position}},
author = {
Mörth, Eric
and
Raidou, Renata Georgia
and
Viola, Ivan
and
Smit, Noeska
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191245}
}
@inproceedings{
10.2312:vcbm.20191247,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Hybrid Visualization of Protein-Lipid and Protein-Protein Interaction}},
author = {
Alharbi, Naif
and
Krone, Michael
and
Chavent, Matthieu
and
Laramee, Robert S.
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191247}
}
@inproceedings{
10.2312:vcbm.20191248,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Molecular Sombreros: Abstract Visualization of Binding Sites within Proteins}},
author = {
Schatz, Karsten
and
Krone, Michael
and
Bauer, Tabea L.
and
Ferrario, Valerio
and
Pleiss, Jürgen
and
Ertl, Thomas
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191248}
}
@inproceedings{
10.2312:vcbm.20191249,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Interactive CPU-based Ray Tracing of Solvent Excluded Surfaces}},
author = {
Rau, Tobias
and
Zahn, Sebastian
and
Krone, Michael
and
Reina, Guido
and
Ertl, Thomas
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191249}
}
@inproceedings{
10.2312:vcbm.20191250,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Evolutionary Pathlines for Blood Flow Exploration in Cerebral Aneurysms}},
author = {
Behrendt, Benjamin
and
Engelke, Wito
and
Berg, Philipp
and
Beuing, Oliver
and
Preim, Bernhard
and
Hotz, Ingrid
and
Saalfeld, Sylvia
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191250}
}
@inproceedings{
10.2312:vcbm.20191251,
booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine},
editor = {
Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
}, title = {{
Distance Field Visualization and 2D Abstraction of Vessel Tree Structures with on-the-fly Parameterization}},
author = {
Lichtenberg, Nils
and
Krayer, Bastian
and
Hansen, Christian
and
Müller, Stefan
and
Lawonn, Kai
}, year = {
2019},
publisher = {
The Eurographics Association},
ISSN = {2070-5786},
ISBN = {978-3-03868-081-9},
DOI = {
10.2312/vcbm.20191251}
}

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  • Item
    VCBM 2019: Frontmatter
    (Eurographics Association, 2019) Kozlíková, Barbora; Raidou, Renata Georgia; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
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    SpectraMosaic: An Exploratory Tool for the Interactive Visual Analysis of Magnetic Resonance Spectroscopy Data
    (The Eurographics Association, 2019) Garrison, Laura; Vašíček, Jakub; Grüner, Renate; Smit, Noeska N.; Bruckner, Stefan; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    Magnetic resonance spectroscopy (MRS) allows for assessment of tissue metabolite characteristics used often for early detection and treatment evaluation of brain-related pathologies. However, a steep learning curve for metabolite interpretation, paired with limited visualization tools, have constrained the more widespread adoption of MRS in clinical practice. In this design study, we collaborated with domain experts to design a novel visualization tool for the exploration of tissue metabolite concentration ratios in MRS clinical and research studies. We present a data and task analysis for this domain, with categorization of MRS data attributes into tiers of visual priority. We furthermore introduce a novel set of visual encodings for these attributes. Our result is SpectraMosaic (Figure 1), an interactive insight-generation tool for rapid exploration and comparison of metabolite ratios. We validate our approach with two case studies from MR spectroscopy experts, providing early qualitative evidence of the efficacy of the system and affording deeper insights into these complex data.
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    Colonic Content Assessment from MRI Imaging Using a Semi-automatic Approach
    (The Eurographics Association, 2019) Ceballos, Victor; Monclús, Eva; Vázquez, Pere-Pau; Bendezú, Álvaro; Mego, Marianela; Merino, Xavier; Azpiroz, Fernando; Navazo, Isabel; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    The analysis of the morphology and content of the gut is necessary in order to achieve a better understanding of its metabolic and functional activity. Magnetic resonance imaging (MRI) has become an important imaging technique since it is able to visualize soft tissues in an undisturbed bowel using no ionizing radiation. In the last few years, MRI of gastrointestinal function has advanced substantially. However, few studies have focused on the colon, because the analysis of colonic content is time consuming and cumbersome. This paper presents a semi-automatic segmentation tool for the quantitative assessment of the unprepared colon from MRI images. The techniques developed here have been crucial for a number of clinical experiments.
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    Multiparametric Magnetic Resonance Image Synthesis using Generative Adversarial Networks
    (The Eurographics Association, 2019) Haarburger, Christoph; Horst, Nicolas; Truhn, Daniel; Broeckmann, Mirjam; Schrading, Simone; Kuhl, Christiane; Merhof, Dorit; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    Generative adversarial networks have been shown to alleviate the problem of limited training data for supervised learning problems in medical image computing. However, most generative models for medical images focus on image-to-image translation rather than de novo image synthesis. In many clinical applications, image acquisition is multiparametric, i.e. includes contrast-enchanced or diffusion-weighted imaging. We present a generative adversarial network that synthesizes a sequence of temporally consistent contrast-enhanced breast MR image patches. Performance is evaluated quantitatively using the Fréchet Inception Distance, achieving a minimum FID of 21.03. Moreover, a qualitative human reader test shows that even a radiologist cannot differentiate between real and fake images easily.
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    A Web-based Application for the Visual Exploration of Colon Morphology Data
    (The Eurographics Association, 2019) Males, Jan; Monclús, Eva; Díaz, Jose; Vázquez, Pere-Pau; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    The colon is an organ whose constant motility poses difficulties to its analysis. Although morphological data can be successfully extracted from Computational Tomography, its radiative nature makes it only indicated for patients with disorders. Only recently, acquisition techniques that rely on the use of Magnetic Resonance Imaging have matured enough to enable the generation of morphological colon data of healthy patients without preparation (i. e. administration of drugs or contrast agents). As a result, a database of colon morphological data for patients under different diets, has been created. Currently, the digestologists we collaborate with analyze the measured data of the gut by inspecting a set of spreadsheets. In this paper, we propose a system for the exploratory visual analysis of the whole database of morphological data at once. It provides features for the visual comparison of data correlations, the inspection of the morphological measures, as well 3D rendering of the colon segmented models. The system solely relies on the use of web technologies, which makes it portable even to mobile devices.
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    Interactive Formation of Statistical Hypotheses in Diffusion Tensor Imaging
    (The Eurographics Association, 2019) Abbasloo, Amin; Wiens, Vitalis; Schmidt-Wilcke, Tobias; Sundgren, Pia; Klein, Reinhard; Schultz, Thomas; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    When Diffusion Tensor Imaging (DTI) is used in clinical studies, statistical hypothesis testing is the standard approach to establish significant differences between groups, such as patients and healthy controls. However, diffusion tensors contain six degrees of freedom, and the most commonly used univariate tests reduce them to a single scalar, such as Fractional Anisotropy. Multivariate tests that account for the full tensor information have been developed, but have not been widely adopted in practice. Based on analyzing the limitations of existing univariate and multivariate tests, we argue that it is beneficial to use a more flexible, steerable test. Therefore, we introduce a test that can be customized to include any subset of tensor attributes that are relevant to the analysis task at hand. We also present a visual analytics system that supports the exploratory task of customizing it to a specific scenario. Our system closely integrates quantitative analysis with suitable visualizations. It links spatial and abstract views to reveal clusters of strong differences, to relate them to the affected anatomical structures, and to visually compare the results of different tests. A use case is presented in which our system leads to the formation of several new hypotheses about the effects of systemic lupus erythematosus on water diffusion in the brain.
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    Semantic Segmentation of Brain Tumors in MRI Data Without any Labels
    (The Eurographics Association, 2019) Weninger, Leon; Krauhausen, Imke; Merhof, Dorit; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    Brain MR images are one of the most important instruments for diagnosing neurological disorders such as tumors, infections or trauma. In particular, grade I-IV brain tumors are a well-studied subject for supervised deep learning approaches. However, for a clinical use of these approaches, a very large annotated database that covers all of the occurring variance is necessary. As MR scanners are not quantitative, it is unclear how good supervised approaches, trained on a specific database, will actually perform on a new set of images that may stem from a yet other scanner. We propose a new method for brain tumor segmentation, that can not only identify abnormal regions, but can also delineate brain tumors into three characteristic radiological areas: The edema, the enhancing core, and the non-enhancing and necrotic tissue. Our concept is based on FLAIR and T1CE MRI sequences, where abnormalities are detected with a variational autoencoder trained on healthy examples. The detected areas are finally postprocessed via Gaussian Mixture Models and finally classified according to the three defined labels. We show results on the BraTS2018 dataset and compare these to previously published unsupervised segmentation results as well as to the results of the BraTS challenge 2018. Our developed unsupervised anomaly detection approach is on par with previously published methods. Meanwhile, the semantic segmentation - a new and unique model - shows encouraging results.
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    Feasibility Study For Automatic Bird Tracking and Visualization from Time-Dependent Marine Radar Imagery
    (The Eurographics Association, 2019) Ganglberger, Florian; Bühler, Katja; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    In recent years, radar technology has increasingly been used for the monitoring of bird migration. Marine radars are often utilized for this purpose because of their wide accessibility, range, and resolution. They allow the tracking of birds even at night-when most bird migration takes place-over extended periods of time. This creates a wealth of radar images, for which manual annotation of bird tracks is not feasible. We propose a tool for automatic bird tracking and visualization from marine radar imagery. For this purpose, we developed a bird tracking algorithm for vertically recorded radar images that is able to extract quantitative parameters including flight direction, height, and duration. The results can be qualitatively verified by a visualization design that enables domain experts the time-dependent visualization of bird tracks. Furthermore, it allows a preprocessing of radar images taken by screen capturing for device independence. Our tool was used in an ornithological monitoring study to analyze over 200.000 vertically recorded radar images taken in multiple observation periods and locations.
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    A Visual Environment for Hypothesis Formation and Reasoning in Studies with fMRI and Multivariate Clinical Data
    (The Eurographics Association, 2019) Jönsson, Daniel; Bergström, Albin; Forsell, Camilla; Simon, Rozalyn; Engström, Maria; Ynnerman, Anders; Hotz, Ingrid; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    We present an interactive visual environment for linked analysis of brain imaging and clinical measurements. The environment is developed in an iterative participatory design process involving neuroscientists investigating the causes of brain-related complex diseases. The hypotheses formation process about correlations between active brain regions and physiological or psychological factors in studies with hundreds of subjects is a central part of the investigation. Observing the reasoning patterns during hypotheses formation, we concluded that while existing tools provide powerful analysis options, they lack effective interactive exploration, thus limiting the scientific scope and preventing extraction of knowledge from available data. Based on these observations, we designed methods that support neuroscientists by integrating their existing statistical analysis of multivariate subject data with interactive visual exploration to enable them to better understand differences between patient groups and the complex bidirectional interplay between clinical measurement and the brain. These exploration concepts enable neuroscientists, for the first time during their investigations, to interactively move between and reason about questions such as 'which clinical measurements are correlated with a specific brain region?' or 'are there differences in brain activity between depressed young and old subjects?'. The environment uses parallel coordinates for effective overview and selection of subject groups, Welch's t-test to filter out brain regions with statistically significant differences, and multiple visualizations of Pearson correlations between brain regions and clinical parameters to facilitate correlation analysis. A qualitative user study was performed with three neuroscientists from different domains. The study shows that the developed environment supports simultaneous analysis of more parameters, provides rapid pathways to insights, and is an effective support tool for hypothesis formation.
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    Pelvis Runner: Visualizing Pelvic Organ Variability in a Cohort of Radiotherapy Patients
    (The Eurographics Association, 2019) Grossmann, Nicolas; Casares-Magaz, Oscar; Muren, Ludvig Paul; Moiseenko, Vitali; Einck, John P.; Gröller, Eduard; Raidou, Renata Georgia; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    In radiation therapy, anatomical changes in the patient might lead to deviations between the planned and delivered dose- including inadequate tumor coverage, and overradiation of healthy tissues. Exploring and analyzing anatomical changes throughout the entire treatment period can help clinical researchers to design appropriate treatment strategies, while identifying patients that are more prone to radiation-induced toxicity. We present the Pelvis Runner, a novel application for exploring the variability of segmented pelvic organs in multiple patients, across the entire radiation therapy treatment process. Our application addresses (i) the global exploration and analysis of pelvic organ shape variability in an abstracted tabular view and (ii) the local exploration and analysis thereof in anatomical 2D/3D views, where comparative and ensemble visualizations are integrated. The workflow is based on available retrospective cohort data, which incorporate segmentations of the bladder, the prostate, and the rectum through the entire radiation therapy process. The Pelvis Runner is applied to four usage scenarios, which were conducted with two clinical researchers, i.e., medical physicists. Our application provides clinical researchers with promising support in demonstrating the significance of treatment plan adaptation to anatomical changes.
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    preha: Establishing Precision Rehabilitation with Visual Analytics
    (The Eurographics Association, 2019) Bernold, Georg; Matkovic, Kresimir; Gröller, Eduard; Raidou, Renata Georgia; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    This design study paper describes preha, a novel visual analytics application in the field of in-patient rehabilitation. We conducted extensive interviews with the intended users, i.e., engineers and clinical rehabilitation experts, to determine specific requirements of their analytical process.We identified nine tasks, for which suitable solutions have been designed and developed in the flexible environment of kibana. Our application is used to analyze existing rehabilitation data from a large cohort of 46,000 patients, and it is the first integrated solution of its kind. It incorporates functionalities for data preprocessing (profiling, wrangling and cleansing), storage, visualization, and predictive analysis on the basis of retrospective outcomes. A positive feedback from the first evaluation with domain experts indicates the usefulness of the newly proposed approach and represents a solid foundation for the introduction of visual analytics to the rehabilitation domain.
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    MedUse: A Visual Analysis Tool for Medication Use Data in the ABCD Study
    (The Eurographics Association, 2019) Bartsch, Hauke; Garrison, Laura; Bruckner, Stefan; Wang, Ariel; Tapert, Susan F.; Grüner, Renate; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    The RxNorm vocabulary is a yearly-published biomedical resource providing normalized names for medications. It is used to capture medication use in the Adolescent Brain Cognitive Development (ABCD) study, an active and publicly available longitudinal research study following 11,800 children over 10 years. In this work, we present medUse, a visual tool allowing researchers to explore and analyze the relationship of drug category to cognitive or imaging derived measures using ABCD study data. Our tool provides position-based context for tree traversal and selection granularity of both study participants and drug category. Developed as part of the Data Exploration and Analysis Portal (DEAP), medUse is available to more than 600 ABCD researchers world-wide. By integrating medUse into an actively used research product we are able to reach a wide audience and increase the practical relevance of visualization for the biomedical field.
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    A Visual Analytics Approach for Patient Stratification and Biomarker Discovery
    (The Eurographics Association, 2019) Alemzadeh, Shiva; Kromp, Florian; Preim, Bernhard; Taschner-Mandl, Sabine; Bühler, Katja; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    We introduce discoVA as a visual analytics tool for the refinement of risk stratification of cancer patients and biomarker discovery. Currently, tools for the joint analysis of multiple biological and clinical information in this field are insufficient or lacking. Our tool fills this gap by enabling bio-medical experts to explore datasets of cancer patient cohorts. By using multiple coordinated visualization techniques, nested visual queries on various data types can be performed to generate/prove a hypothesis by identifying discrete sub-cohorts. We demonstrated the utility of discoVA by a case study involving bio-medical researchers.
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    DockVis: Visual Analysis of Molecular Docking Data
    (The Eurographics Association, 2019) Furmanová, Katarína; Kozlíková, Barbora; Vonásek, Vojtěch; Byška, Jan; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    Molecular docking is one of the key mechanisms for predicting possible interactions between ligands and proteins. This highly complex task can be simulated by several software tools, providing the biochemists with possible ligand trajectories, which have to be subsequently explored and evaluated for their biochemical relevance. This paper focuses on aiding this exploration process by introducing DockVis visual analysis tool. DockVis operates primarily with the multivariate output data from one of the latest available tools for molecular docking, CaverDock. CaverDock output consists of several parameters and properties, which have to be subsequently studied and understood. DockVis was designed in tight collaboration with protein engineers using the CaverDock tool. However, we believe that the concept of DockVis can be extended to any other molecular docking tool providing the users with corresponding computation results.
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    Interactive Exploded Views for Molecular Structures
    (The Eurographics Association, 2019) Sbardellati, Maximilian; Miao, Haichao; WU, Hsiang-Yun; Groeller, Eduard; Barisic, Ivan; Viola, Ivan; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    We propose an approach to interactively create exploded views of molecular structures with the goal to help domain experts in their design process and provide them with a meaningful visual representation of component relationships. Exploded views are excellently suited to manage visual occlusion of structure components, which is one of the main challenges when visualizing complex 3D data. In this paper, we discuss four key parameters of an exploded view: explosion distance, direction, order, and the selection of explosion components. We propose two strategies, namely the structure-derived exploded view and the interactive free-form exploded view, for computing these four parameters systematically. The first strategy allows scientists to automatically create exploded views by computing the parameters from the given object structures. The second strategy further supports them to design and customize detailed explosion paths through user interaction. Our approach features the possibility to animate exploded views, to incorporate ease functions into these animations and to display the explosion path of components via arrows. Finally, we demonstrate three use cases with various challenges that we investigated in collaboration with a domain scientist. Our approach, therefore, provides interesting new ways of investigating and presenting the design layout and composition of complex molecular structures.
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    Layer-Aware iOCT Volume Rendering for Retinal Surgery
    (The Eurographics Association, 2019) Weiss, Jakob; Eck, Ulrich; Nasseri, Muhamad Ali; Maier, Mathias; Eslami, Abouzar; Navab, Nassir; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    Retinal microsurgery is one of the most challenging types of surgery, yet in practice, intraoperative digital assistance is rare. The introduction of fast, microscope integrated Optical Coherence Tomography (iOCT) has enabled intraoperative imaging of subsurface structures. However, effective intraoperative visualization of this data poses a challenging problem both in terms of performance and engineering as well as for creating easily interpretable visualizations of this data. Most existing research focuses on visualization of diagnostic OCT data where imaging quality is higher and processing times are not an issue. We introduce a perceptually linear color map for a separated encoding of tissue reflectivity and positional information as chrominance and luminance. Based on this color mapping, we propose a Direct Volume Rendering (DVR) method that aids structure perception. To aid subretinal injection tasks, we introduce a novel Layer-Adjusted Maximum Intensity Projection (LA-MIP), correcting for the natural curvature of the retinal tissue. Expert feedback suggests our methods are preferred over baseline methods. Further research is needed to confirm the benefits of our approach in routine clinical applications.
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    Medical Animations: A Survey and a Research Agenda
    (The Eurographics Association, 2019) Preim, Bernhard; Meuschke, Monique; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    Animation is a potentially powerful instrument to convey complex information with movements, smooth transitions between different states that employ the strong human capabilities to perceive and interpret motion. Animation is a natural choice to display time-dependent data where the dynamic nature of the data is mapped to a kind of video (temporal animation). Clipping planes may be smoothly translated and object transparency adapted to control visibility and further support emphasis of spatial relations, e.g. around a tumor. Animation, however, may also be employed for static data, e.g. to move a camera along a predefined path to convey complex anatomical structures. Virtual endoscopy, where the virtual camera is moved inside an air-filled or fluid-filled structure is a prominent example for these non-temporal animations. Animations, however, are complex visualizations that may depict a larger number of changes in a short period of time. Thus, they need to be assessed in their capability to actually convey information. In this paper, we give a survey of temporal and non-temporal animated visualizations focussed on medical applications and discuss the research potential that arises. To be employed more widely, cognitive limitations, e.g. change blindness, need to be considered. The reduction of complexity in temporal animations is an essential topic to enable the detection and interpretation of changes. Emphasis techniques may guide the user's attention and improve the perception of essential features. Finally, interaction beyond the typical video recorder functionality is considered. Although our focus is medicine, the discussion of a research agenda is partially based on cartography, where animation is widely used.
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    Using Position-Based Dynamics for Simulating the Mitral Valve in a Decision Support System
    (The Eurographics Association, 2019) Walczak, Lars; Georgii, Joachim; Tautz, Lennart; Neugebauer, Mathias; Wamala, Isaac; Sündermann, Simon; Falk, Volkmar; Hennemuth, Anja; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    In mitral valve interventions, surgeons have to select an optimal combination of techniques for every patient. Especially less experienced physicians would benefit from decision support for this process. To support the visual analysis of the patientspecific valvular dynamics and an in-silico pre-intervention simulation of different therapy options, a real-time simulation of the mitral valve is needed, especially for the use in a time-constrained clinical environment. We develop a simplified model of the mitral valve and propose a novel approach to simulate the mitral valve with position-based dynamics. As input, a mesh representation of the open-state mitral valve, two polygons representing the open and closed annulus states, simplified chordae tendineae, and a set of forces for approximating the surrounding blood are required. The mitral valve model can be deformed to simulate the closing and opening as well as incorporate changes caused by virtual interventions in the simulation. For evaluation, ten mitral valves were reconstructed from transesophageal echocardiogram sequences of patients with normal and abnormal physiology. Experts in cardiac surgery annotated anatomical landmarks for valve reconstruction. The simulation results for closing the valve were qualitatively compared to the anatomy depicted in the image sequences and, if present, the reproduction of a prolapse was verified. In addition, two virtual interventions (annuloplasty and clipping) were performed for one case and provided new insights about changes in valve closure and orifice area after modification. Each simulation ran at interactive frame rates. Our approach enables an efficient simulation of the mitral valve with normal and abnormal valve closing behavior as well as virtual interventions. The simulation results showed good agreements with the image data in general and reproduced valve closure in all cases. In three cases, prolapse was not or not correctly reproduced. Further research is needed to parameterize the model in pathologic cases.
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    Visual Analytics in Digital Pathology: Challenges and Opportunities
    (The Eurographics Association, 2019) Corvò, Alberto; Westenberg, Michel A.; Wimberger-Friedl, Reinhold; Fromme, Stephan; Peeters, Michel M. R.; Driel, Marc A. van; Wijk, Jarke J. van; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    The advances in high-throughput digitization, digital pathology systems, and quantitative image analysis opened new horizons in pathology. The diagnostic work of the pathologists and their role is likely to be augmented with computer-assistance and more quantitative information at hand. The recent success of artificial intelligence (AI) and computer vision methods demonstrated that in the coming years machines will support pathologists in typically tedious and highly subjective tasks and also in better patient stratification. In spite of clear future improvements in the diagnostic workflow, questions on how to effectively support the pathologists and how to integrate current data sources and quantitative information still persist. In this context, Visual Analytics (VA) - as the discipline that aids users to solve complex problems with an interactive and visual approach - can play a vital role to support the cognitive skills of pathologists and the large volumes of data available. To identify the main opportunities to employ VA in digital pathology systems, we conducted a survey with 20 pathologists to characterize the diagnostic practice and needs from a user perspective. From our findings, we discuss how VA can leverage quantitative image data to empower pathologists with new advanced digital pathology systems.
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    InkVis: A High-Particle-Count Approach for Visualization of Phase-Contrast Magnetic Resonance Imaging Data
    (The Eurographics Association, 2019) de Hoon, Niels; Lawonn, Kai; Jalba, Andrei; Eisemann, Elmar; Vilanova, Anna; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    Phase-Contrast Magnetic Resonance Imaging (PC-MRI) measures volumetric and time-varying blood flow data, unsurpassed in quality and completeness. Such blood-flow data have been shown to have the potential to improve both diagnosis and risk assessment of cardiovascular diseases (CVDs) uniquely. Typically PC-MRI data is visualized using stream- or pathlines. However, time-varying aspects of the data, e.g., vortex shedding, breakdown, and formation, are not sufficiently captured by these visualization techniques. Experimental flow visualization techniques introduce a visible medium, like smoke or dye, to visualize flow aspects including time-varying aspects. We propose a framework that mimics such experimental techniques by using a high number of particles. The framework offers great flexibility which allows for various visualization approaches. These include common traditional flow visualizations, but also streak visualizations to show the temporal aspects, and uncertainty visualizations. Moreover, these patient-specific measurements suffer from noise artifacts and a coarse resolution, causing uncertainty. Traditional flow visualizations neglect uncertainty and, therefore, may give a false sense of certainty, which can mislead the user yielding incorrect decisions. Previously, the domain experts had no means to visualize the effect of the uncertainty in the data. Our framework has been adopted by domain experts to visualize the vortices present in the sinuses of the aorta root showing the potential of the framework. Furthermore, an evaluation among domain experts indicated that having the option to visualize the uncertainty contributed to their confidence on the analysis.
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    Robustness Evaluation of CFD Simulations to Mesh Deformation
    (The Eurographics Association, 2019) Scheid-Rehder, Alexander; Lawonn, Kai; Meuschke, Monique; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    CFD simulations are an increasingly important method for the non-invasive analysis of risk factors for aneurysm rupture. Their robustness, however, has to be examined more thoroughly before clinical use is possible. We present a novel framework that enables robustness evaluation of CFD simulation according to mesh deformation on patient-specific blood vessel geometry. Our tool offers a guided workflow to generate, run, and visualize OpenFOAM simulations, which significantly decreases the usual overhead of CFD simulations with OpenFOAM. Besides, the deformation of the original geometry allows the user to evaluate the robustness of the simulation without the need to repeat expensive operations of the data pre-processing phase. We assessed the robustness of CFD simulations by applying our framework to several aneurysm data sets.
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    HIFUpm: a Visual Environment to Plan and Monitor High Intensity Focused Ultrasound Treatments
    (The Eurographics Association, 2019) Modena, Daniela; Bassano, Davide; Elevelt, Aaldert; Baragona, Marco; Hilbers, Peter A. J.; Westenberg, Michel A.; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    High Intensity Focused Ultrasound (HIFU) is a non invasive therapeutic method, which has been a subject of interest for the treatment of various kinds of tumors. Despite the numerous advantages, HIFU techniques do not reach the high delivery precision like other therapies (e.g., radiotherapy). For this reason, a correct therapy planning and monitoring in HIFU treatments remains a challenge. We propose HIFUpm, a visual analytics approach which enables the visualization of the HIFU simulation results, while guiding the user in the evaluation of the procedure. We illustrate the use of HIFUpm for an ablative treatment of an osteoid osteoma. This use case demonstrates that HIFUpm provides a flexible visual environment to plan and monitor HIFU procedures.
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    The Vitruvian Baby: Interactive Reformation of Fetal Ultrasound Data to a T-Position
    (The Eurographics Association, 2019) Mörth, Eric; Raidou, Renata Georgia; Viola, Ivan; Smit, Noeska; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    Three-dimensional (3D) ultrasound imaging and visualization is often used in medical diagnostics, especially in prenatal screening. Screening the development of the fetus is important to assess possible complications early on. State of the art approaches involve taking standardized measurements to compare them with standardized tables. The measurements are taken in a 2D slice view, where precise measurements can be difficult to acquire due to the fetal pose. Performing the analysis in a 3D view would enable the viewer to better discriminate between artefacts and representative information. Additionally making data comparable between different investigations and patients is a goal in medical imaging techniques and is often achieved by standardization. With this paper, we introduce a novel approach to provide a standardization method for 3D ultrasound fetus screenings. Our approach is called ''The Vitruvian Baby'' and incorporates a complete pipeline for standardized measuring in fetal 3D ultrasound. The input of the method is a 3D ultrasound screening of a fetus and the output is the fetus in a standardized T-pose. In this pose, taking measurements is easier and comparison of different fetuses is possible. In addition to the transformation of the 3D ultrasound data, we create an abstract representation of the fetus based on accurate measurements. We demonstrate the accuracy of our approach on simulated data where the ground truth is known.
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    Hybrid Visualization of Protein-Lipid and Protein-Protein Interaction
    (The Eurographics Association, 2019) Alharbi, Naif; Krone, Michael; Chavent, Matthieu; Laramee, Robert S.; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    In the Molecular Dynamics (MD) visualization literature, different approaches are utilized to study protein-lipid interactions (PLI) and protein-protein interaction (PPI) in decoupled contexts. However, the two types of interaction occur in the same space-time domain. It is beneficial to study the PLI and PPI in a unified context. Nevertheless, the simulation's size, length, and complexity increase the challenge of understanding the dynamic behavior. We propose a novel framework consisting of four linked views, a time-dependent 3D view, a novel hybrid view, a clustering timeline, and a details-on-demand window. We introduce a selection of visual designs to convey the behavior of PLI and PPI through a unified coordinate system. Abstraction is used to present proteins in hybrid 2D space, a projected tiled space is used to present both PLI and PPI at the particle level in a heat-map style visual design while glyphs are used to represent PPI at the molecular level. We couple visually separable visual designs in a unified coordinate space. The result lets the user study both PLI and PPI separately or together in a unified visual analysis framework. We also exemplify its use with case studies focusing on protein clustering and we report domain expert feedback.
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    Molecular Sombreros: Abstract Visualization of Binding Sites within Proteins
    (The Eurographics Association, 2019) Schatz, Karsten; Krone, Michael; Bauer, Tabea L.; Ferrario, Valerio; Pleiss, Jürgen; Ertl, Thomas; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    We present a novel abstract visualization for the binding sites of proteins. Binding sites play an essential role in enzymatic reactions and are, thus, often investigated in structural biology. They are typically located within cavities. The shape and properties of the cavity influence whether and how easily a substrate can reach the active site where the reaction is triggered. Molecular surface visualizations can help to analyze the accessibility of binding sites, but are typically prone to visual clutter. Our novel abstract visualization shows the cavity containing the binding site as well as the surface region directly surrounding the cavity entrance in a simplified manner. The resulting visualization resembles a hat, where the brim depicts the surrounding surface region and the crown the cavity. Hence, we dubbed our abstraction Molecular Sombrero, using the Spanish term for 'hat'. Our abstraction is less cluttered than traditional molecular surface visualizations. It highlights important parameters, like cavity diameter, by mapping them to the shape of the sombrero. The visual abstraction also facilitates an easy side-by-side comparison of different data sets. We show the applicability of our Molecular Sombreros to different real-world use cases.
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    Interactive CPU-based Ray Tracing of Solvent Excluded Surfaces
    (The Eurographics Association, 2019) Rau, Tobias; Zahn, Sebastian; Krone, Michael; Reina, Guido; Ertl, Thomas; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    Depictions of molecular surfaces such as the Solvent Excluded Surface (SES) can provide crucial insight into functional molecular properties, such as the molecule's potential to react. The interactive visualization of single and multiple molecule surfaces is essential for the data analysis by domain experts. Nowadays, the SES can be rendered at high frame rates using shader-based ray casting on the GPU. However, rendering large molecules or larger molecule complexes requires large amounts of memory that has the potential to exceed the memory limitations of current hardware. Here we show that rendering using CPU ray tracing also reaches interactive frame rates without hard limitations to memory. In our results large molecule complexes can be rendered with only the precomputation of each individual SES, and no further involved representation or transformation. Additionally, we provide advanced visualization techniques like ambient occlusion opacity mapping (AOOM) to enhance the comprehensibility of the molecular structure. CPU ray tracing not only provides very high image quality and global illumination, which is beneficial for the perception of spatial structures, it also opens up the possibility to visualize larger data sets and to render on any HPC cluster. Our results demonstrate that simple instancing of geometry keeps the memory consumption for rendering large molecule complexes low, so the examination of much larger data is also possible.
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    Evolutionary Pathlines for Blood Flow Exploration in Cerebral Aneurysms
    (The Eurographics Association, 2019) Behrendt, Benjamin; Engelke, Wito; Berg, Philipp; Beuing, Oliver; Preim, Bernhard; Hotz, Ingrid; Saalfeld, Sylvia; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    Blood flow simulations play an important role for the understanding of vascular diseases, such as aneurysms. However, analysis of the resulting flow patterns, especially comparisons across patient groups, are challenging. Typically, the hemodynamic analysis relies on trial and error inspection of the flow data based on pathline visualizations and surface renderings. Visualizing too many pathlines at once may obstruct interesting features, e.g., embedded vortices, whereas with too little pathlines, particularities such as flow characteristics in aneurysm blebs might be missed. While filtering and clustering techniques support this task, they require the pre-computation of pathlines densely sampled in the space-time domain. Not only does this become prohibitively expensive for large patient groups, but the results often suffer from undersampling artifacts. In this work, we propose the usage of evolutionary algorithms to reduce the overhead of computing pathlines that do not contribute to the analysis, while simultaneously reducing the undersampling artifacts. Integrated in an interactive framework, it efficiently supports the evaluation of hemodynamics for clinical research and treatment planning in case of cerebral aneurysms. The specification of general optimization criteria for entire patient groups allows the blood flow data to be batch-processed. We present clinical cases to demonstrate the benefits of our approach especially in presence of aneurysm blebs. Furthermore, we conducted an evaluation with four expert neuroradiologists. As a result, we report advantages of our method for treatment planning to underpin its clinical potential.
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    Distance Field Visualization and 2D Abstraction of Vessel Tree Structures with on-the-fly Parameterization
    (The Eurographics Association, 2019) Lichtenberg, Nils; Krayer, Bastian; Hansen, Christian; Müller, Stefan; Lawonn, Kai; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
    In this paper, we make contributions to the visualization of vascular structures. Based on skeletal input data, we provide a combined 2D and implicit 3D visualization of vasculature, that is parameterized on-the-fly for illustrative visualization. We use an efficient algorithm that creates a distance field volume from triangles and extend it to handle skeletal tree data. Spheretracing this volume allows to visualize the vasculature in a flexible way, without the need to recompute the volume. Illustrative techniques, that have been frequently applied to vascular visualizations often require texture coordinates. Therefore, modifying an object-based algorithm, we propose an image-based, hierarchical optimization process that allows to derive periodic texture coordinates in a frame-coherent way and suits the implicit representation of the vascular structures. In addition to the 3D surface visualization, we propose a simple layout algorithm that applies a 2D parameterization to the skeletal tree nodes. This parameterization can be used to color-code the vasculature or to plot a 2D overview-graph, that highlights the branching topology of the skeleton. We transfer measurements, done in 3D space, to the 2D plot in order to avoid visual clutter and self occlusions in the 3D representation. A visual link between the 3D and 2D views is established via color codes and texture patterns. The potential of our pipeline is shown in several prototypical application scenarios.