All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Line Filtering for Surgical Tool Localization in 3D Ultrasound Images

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00212572" target="_blank" >RIV/68407700:21230/13:00212572 - isvavai.cz</a>

  • Result on the web

    <a href="http://cmp.felk.cvut.cz/pub/cmp/articles/kybic/Uhercik-CBM2013.pdf" target="_blank" >http://cmp.felk.cvut.cz/pub/cmp/articles/kybic/Uhercik-CBM2013.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.compbiomed.2013.09.020" target="_blank" >10.1016/j.compbiomed.2013.09.020</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Line Filtering for Surgical Tool Localization in 3D Ultrasound Images

  • Original language description

    We present a method for automatic surgical tool localization in 3D ultrasound images based on line filtering, voxel classification and model fitting. This could possibly provide assistance for biopsy needle or micro-electrode insertion, or a robotic system performing this insertion. The line-filtering method is first used to enhance the contrast of the 3D ultrasound image, then a classifier is chosen to separate the tool voxels, in order to reduce the number of outliers. The last step is Random Sample Consensus (RANSAC) model fitting. Experimental results on several different polyvinyl alcohol (PVA) cryogel data sets demonstrate that the failure rate of the method proposed herein is improved by at least 86% compared to the model-fitting RANSAC algorithm with axis accuracy better than 1 mm, at the expense of only a modest increase in computational effort. The results of this experiment show that this system could be useful for clinical applications.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • 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

    2013

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Computers in Biology and Medicine

  • ISSN

    0010-4825

  • e-ISSN

  • Volume of the periodical

    43

  • Issue of the periodical within the volume

    12

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    10

  • Pages from-to

    2036-2045

  • UT code for WoS article

    000329413800006

  • EID of the result in the Scopus database