Real-Time Dense Nucleus Selection from Confocal Data

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Date
2014
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Selecting structures from volume data using direct over-the-visualization interactions, such as a paint brush, is perhaps the most intuitive method in a variety of application scenarios. Unfortunately, it seems difficult to design a universal tool that is effective for all different structures in biology research. In [WOCH12b], an interactive technique was proposed for extracting neural structures from confocal microscopy data. It uses a dual-stroke paint brush to select desired structures directly from volume visualizations. However, the technique breaks down when it was applied to selecting densely packed structures with condensed shapes, such as nuclei from zebrafish eye development research. We collaborated with biologists studying zebrafish eye development and adapted the paint brush tool for real-time nucleus selection from volume data. The morphological diffusion algorithm used in the previous paint brush is restricted to gradient descending directions for improved nucleus boundary definition. Occluded seeds are removed using backward ray-casting. The adapted paint brush is then used in tracking cell movements in a time sequence dataset of a developing zebrafish eye.
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@inproceedings{
:10.2312/vcbm.20141184
https::/diglib.eg.org/handle/10.2312/vcbm.20141184.059-068
, booktitle = {
Eurographics Workshop on Visual Computing for Biology and Medicine
}, editor = {
Ivan Viola and Katja Buehler and Timo Ropinski
}, title = {{
Real-Time Dense Nucleus Selection from Confocal Data
}}, author = {
Wan, Yong
and
Otsuna, Hideo
and
Kwan, K. M.
and
Hansen, Charles
}, year = {
2014
}, publisher = {
The Eurographics Association
}, ISSN = {
2070-5778
}, ISBN = {
978-3-905674-62-0
}, DOI = {
/10.2312/vcbm.20141184
https://diglib.eg.org/handle/10.2312/vcbm.20141184.059-068
} }
Citation