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
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Czech description
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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
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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
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
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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
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