Crowdsourcing the creation of image segmentation algorithms for connectomics
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F15%3APU116097" target="_blank" >RIV/00216305:26220/15:PU116097 - isvavai.cz</a>
Result on the web
<a href="http://journal.frontiersin.org/Journal/10.3389/fnana.2015.00142/full" target="_blank" >http://journal.frontiersin.org/Journal/10.3389/fnana.2015.00142/full</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3389/fnana.2015.00142" target="_blank" >10.3389/fnana.2015.00142</a>
Alternative languages
Result language
angličtina
Original language name
Crowdsourcing the creation of image segmentation algorithms for connectomics
Original language description
To stimulate progress in automating the reconstruction of neural circuits, we organized the first international challenge on 2D segmentation of electron microscopic (EM) images of the brain. Participants submitted boundary maps predicted for a test set of images, and were scored based on their agreement with a consensus of human expert annotations. The winning team had no prior experience with EM images, and employed a convolutional network. This “deep learning” approach has since become accepted as a standard for segmentation of EM images. The challenge has continued to accept submissions, and the best so far has resulted from cooperation between two teams. The challenge has probably saturated, as algorithms cannot progress beyond limits set by ambiguities inherent in 2D scoring and the size of the test dataset. Retrospective evaluation of the challenge scoring system reveals that it was not sufficiently robust to variations in the widths of neurite borders. We propose a solution to this problem, which should be useful for a future 3D segmentation challenge.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
<a href="/en/project/LO1401" target="_blank" >LO1401: Interdisciplinary Research of Wireless Technologies</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Frontiers in Neuroanatomy
ISSN
1662-5129
e-ISSN
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Volume of the periodical
9
Issue of the periodical within the volume
142
Country of publishing house
CH - SWITZERLAND
Number of pages
13
Pages from-to
1-13
UT code for WoS article
000365846500001
EID of the result in the Scopus database
2-s2.0-84948763339