Line Filtering for Surgical Tool Localization in 3D Ultrasound Images

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Line Filtering for Surgical Tool Localization in 3D Ultrasound Images

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Line Filtering for Surgical Tool Localization in 3D Ultrasound Images

Popis výsledku anglicky

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.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

<a href="/cs/project/GAP202%2F11%2F0111" target="_blank" >GAP202/11/0111: Automatická analýza obrazů nervové tkáně ze světelné a elektronové mikroskopie</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název periodika

Computers in Biology and Medicine

ISSN

0010-4825

e-ISSN

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Svazek periodika

43

Číslo periodika v rámci svazku

12

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

10

Strana od-do

2036-2045

Kód UT WoS článku

000329413800006

EID výsledku v databázi Scopus

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