Polar Space Based Shape Averaging for Star-shaped Biological Objects

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dc.contributor.authorRuzaeva, Karinaen_US
dc.contributor.authorNöh, Katharinaen_US
dc.contributor.authorBerkels, Benjaminen_US
dc.contributor.editorOeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomasen_US
dc.date.accessioned2021-09-21T08:09:24Z
dc.date.available2021-09-21T08:09:24Z
dc.date.issued2021
dc.description.abstractIn this paper, we propose an averaging method for expert segmentation proposals of microbial organisms, resulting in a smooth, naturally looking segmentation ground truth. The approach exploits a geometrical property of the majority of the organisms - star-shapedness - and is based on contour averaging in polar space. It is robust and computationally efficient, where robustness is due to the absence of tuneable parameters. Moreover, the algorithm preserves the uncertainty (in terms of the standard deviation) of the experts' opinion, which allows to introduce an uncertainty-aware metric for estimation of the segmentation quality. This metric emphasizes the influence of ground truth regions with low variance. We study the performance of the proposed averaging method on time-lapse microscopy data of Corynebacterium glutamicum and the uncertainty-aware metric on synthetic data.en_US
dc.description.sectionheadersGetting an overview in bio (and medicine)
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.identifier.doi10.2312/vcbm.20211340
dc.identifier.isbn978-3-03868-140-3
dc.identifier.issn2070-5786
dc.identifier.pages13-17
dc.identifier.urihttps://doi.org/10.2312/vcbm.20211340
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20211340
dc.publisherThe Eurographics Associationen_US
dc.subjectApplied computing
dc.subjectImaging
dc.subjectComputing methodologies
dc.subjectImage processing
dc.titlePolar Space Based Shape Averaging for Star-shaped Biological Objectsen_US
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VCBM 2021: Eurographics Workshop on Visual Computing for Biology and Medicine