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@PROCEEDINGS{Ruzaeva:901793,
author = {Ruzaeva, Karina and Nöh, Katharina and Berkels, Benjamin},
title = {{P}olar {S}pace {B}ased {S}hape {A}veraging for
{S}tar-shaped {B}iological {O}bjects},
publisher = {The Eurographics Association},
reportid = {FZJ-2021-03826},
year = {2021},
abstract = {In 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.},
month = {Sep},
date = {2021-09-28},
organization = {Eurographics Workshop on Visual
Computing for Biology and Medicine,
virtual (Germany), 28 Sep 2021 - 1 Oct
2021},
keywords = {Applied computing (Other) / Imaging (Other) / Computing
methodologies (Other) / Image processing (Other)},
cin = {IBG-1},
cid = {I:(DE-Juel1)IBG-1-20101118},
pnm = {2171 - Biological and environmental resources for
sustainable use (POF4-217)},
pid = {G:(DE-HGF)POF4-2171},
typ = {PUB:(DE-HGF)26},
doi = {10.2312/VCBM.20211340},
url = {https://juser.fz-juelich.de/record/901793},
}