Visual Analytics for the Exploration and Assessment of Segmentation Errors

Simple item page
dc.contributor.authorRaidou, Renata G.en_US
dc.contributor.authorMarcelis, Freek J. J.en_US
dc.contributor.authorBreeuwer, Marcelen_US
dc.contributor.authorGröller, Eduarden_US
dc.contributor.authorVilanova, Annaen_US
dc.contributor.authorWetering, Huub M. M. van deen_US
dc.contributor.editorStefan Bruckner and Bernhard Preim and Anna Vilanova and Helwig Hauser and Anja Hennemuth and Arvid Lundervolden_US
dc.date.accessioned2016-09-07T05:38:06Z
dc.date.available2016-09-07T05:38:06Z
dc.date.issued2016
dc.description.abstractSeveral diagnostic and treatment procedures require the segmentation of anatomical structures from medical images. However, the automatic model-based methods that are often employed, may produce inaccurate segmentations. These, if used as input for diagnosis or treatment, can have detrimental effects for the patients. Currently, an analysis to predict which anatomic regions are more prone to inaccuracies, and to determine how to improve segmentation algorithms, cannot be performed. We propose a visual tool to enable experts, working on model-based segmentation algorithms, to explore and analyze the outcomes and errors of their methods. Our approach supports the exploration of errors in a cohort of pelvic organ segmentations, where the performance of an algorithm can be assessed. Also, it enables the detailed exploration and assessment of segmentation errors, in individual subjects. To the best of our knowledge, there is no other tool with comparable functionality. A usage scenario is employed to explore and illustrate the capabilities of our visual tool. To further assess the value of the proposed tool, we performed an evaluation with five segmentation experts. The evaluation participants confirmed the potential of the tool in providing new insight into their data and employed algorithms. They also gave feedback for future improvements.en_US
dc.description.sectionheadersSimulation and Visual Analysis in Medicine
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.identifier.doi10.2312/vcbm.20161287
dc.identifier.isbn978-3-03868-010-9
dc.identifier.issn2070-5786
dc.identifier.pages193-202
dc.identifier.urihttps://doi.org/10.2312/vcbm.20161287
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20161287
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.8 [Computer Graphics]
dc.subjectApplications
dc.subjectApplications
dc.subject
dc.subjectJ.3 [Computer Applications]
dc.subjectLife and Medical Sciences
dc.subjectLife and Medical Sciences
dc.titleVisual Analytics for the Exploration and Assessment of Segmentation Errorsen_US
Files
Original bundle
Now showing 1 - 4 of 4
Thumbnail Image
Name:
193-202.pdf
Size:
7.73 MB
Format:
Adobe Portable Document Format
Download
No Thumbnail Available
Name:
demo_fin.mp4
Size:
63.74 MB
Format:
Unknown data format
Download
No Thumbnail Available
Name:
evaluation_material.zip
Size:
577.9 KB
Format:
Zip file
Download
No Thumbnail Available
Name:
figures.zip
Size:
2.56 MB
Format:
Zip file
Download
Collections
VCBM 16: Eurographics Workshop on Visual Computing for Biology and Medicine