Trainable Segmentation Based on Local-level and Segment-level Feature Extraction

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F12%3APU100206" target="_blank" >RIV/00216305:26220/12:PU100206 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Trainable Segmentation Based on Local-level and Segment-level Feature Extraction
Original language description
This paper deals with the segmentation of neuronal struc- tures in electron microscope (EM) stacks, which is one of the challenges of the ISBI 2012 conference. The data for the challenge consists of a stack of 30 EM slices for training and 30 EM stacks for testing. The training data was labelled by an expert human neuroanatomist. In this paper a segmentation using local-level and segment-level features and machine learning algorithms was used. The results achieved on the ISBI 2012 challenge test set were: the Rand error: 0.139038440, warping er- ror: 0.002641296 and pixel error: 0.102285508. The main criterion for segmentation evaluation was the Rand error.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
IEEE International Symposium on Biomedical Imaging
ISBN
978-1-4673-1118-2
ISSN
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e-ISSN
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Number of pages
63
Pages from-to
17-24
Publisher name
Neuveden
Place of publication
Barcelona
Event location
Barcelona
Event date
May 2, 2012
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000308143100071

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