Neuromuscular fiber segmentation using particle filtering and discrete optimization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00200726" target="_blank" >RIV/68407700:21230/12:00200726 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Neuromuscular fiber segmentation using particle filtering and discrete optimization
Original language description
'We present an algorithm to segment a set of parallel, intertwined and bifurcating fibers from 3D images, targeted for identification of neuronal fibers in very large sets of 3D confocal microscopy images. The method consists of preprocessing, local calculation of fiber probabilities, seed detection, local tracking by particle filtering, global supervised seed clustering, and final voxel segmentation. The preprocessing uses a novel random local probability filtering segmentation. The global segmentationis solved by discrete optimization. The combination of global and local approaches makes the segmentation robust, yet the individual data blocks can be processed sequentially, limiting memory consumption. The method is automatic but efficient manual interaction is possible if needed. Initial promising results on a neuromuscular projection fiber dataset as well as on simulated data are presented.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GAP202%2F11%2F0111" target="_blank" >GAP202/11/0111: Automatic analysis of light and electron microscopy neuronal data</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů