Study of Shape Fusion Algorithms for 3D Time-Lapse Microscopy

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F25%3A00144299" target="_blank" >RIV/00216224:14330/25:00144299 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/10980908" target="_blank" >https://ieeexplore.ieee.org/document/10980908</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ISBI60581.2025.10980908" target="_blank" >10.1109/ISBI60581.2025.10980908</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Study of Shape Fusion Algorithms for 3D Time-Lapse Microscopy

Popis výsledku v původním jazyce

In biomedical image processing, reference data used to benchmark segmentation algorithms are typically obtained by fusing expert annotations. We compare popular fusion algorithms (majority voting, STAPLE, and Robust Bayesian Fusion) and study (1) how their results depend on the variability of input annotations and (2) how well they preserve shapes w.r.t, biologically relevant measures (BRM) such as volume and average roundness. We also study (3) the correlation between BRM and measures common in image processing (namely, Jaccard index and Hausdorff distance). For our experiments, we created 3D time-lapse segmentation annotations of migrating cells with complex dynamic shapes (Fluo-C3DL-MDA231 dataset from the Cell Tracking Challenge). The full annotations are publicly available. The study found that none of the selected methods produced satisfactory results w.r.t. BRM, highlighting the need for new methods.

Název v anglickém jazyce

Study of Shape Fusion Algorithms for 3D Time-Lapse Microscopy

Popis výsledku anglicky

In biomedical image processing, reference data used to benchmark segmentation algorithms are typically obtained by fusing expert annotations. We compare popular fusion algorithms (majority voting, STAPLE, and Robust Bayesian Fusion) and study (1) how their results depend on the variability of input annotations and (2) how well they preserve shapes w.r.t, biologically relevant measures (BRM) such as volume and average roundness. We also study (3) the correlation between BRM and measures common in image processing (namely, Jaccard index and Hausdorff distance). For our experiments, we created 3D time-lapse segmentation annotations of migrating cells with complex dynamic shapes (Fluo-C3DL-MDA231 dataset from the Cell Tracking Challenge). The full annotations are publicly available. The study found that none of the selected methods produced satisfactory results w.r.t. BRM, highlighting the need for new methods.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10200 - Computer and information sciences

Projekt

<a href="/cs/project/GA21-20374S" target="_blank" >GA21-20374S: Segmentace a sledování buněk se složitým tvarem</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings - International Symposium on Biomedical Imaging

ISBN

9798331520526

ISSN

1945-7928

e-ISSN

—

Počet stran výsledku

5

Strana od-do

1-5

Název nakladatele

IEEE Computer Society

Místo vydání

ISBI 2025

Místo konání akce

Houston, TX, USA

Datum konání akce

14. 4. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001546451000235