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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

  • DOI - Digital Object Identifier

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

  • Czech description

Classification

  • Type

    O - Miscellaneous

  • CEP classification

    JD - Use of computers, robotics and its application

  • OECD FORD branch

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