Fast and robust semi-automatic liver segmentation with haptic interaction.
Identifieur interne : 005E28 ( Main/Merge ); précédent : 005E27; suivant : 005E29Fast and robust semi-automatic liver segmentation with haptic interaction.
Auteurs : Erik Vidholm [Suède] ; Sven Nilsson ; Ingela NyströmSource :
- Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention ; 2006.
English descriptors
- KwdEn :
- Algorithms, Artificial Intelligence, Computer Simulation, Hepatectomy (methods), Humans, Imaging, Three-Dimensional (methods), Liver (radiography), Liver (surgery), Models, Biological, Pattern Recognition, Automated (methods), Radiographic Image Enhancement (methods), Radiographic Image Interpretation, Computer-Assisted (methods), Reproducibility of Results, Sensitivity and Specificity, Surgery, Computer-Assisted (methods), Touch, User-Computer Interface.
- MESH :
- methods : Hepatectomy, Imaging, Three-Dimensional, Pattern Recognition, Automated, Radiographic Image Enhancement, Radiographic Image Interpretation, Computer-Assisted, Surgery, Computer-Assisted.
- radiography : Liver.
- surgery : Liver.
- Algorithms, Artificial Intelligence, Computer Simulation, Humans, Models, Biological, Reproducibility of Results, Sensitivity and Specificity, Touch, User-Computer Interface.
Abstract
We present a method for semi-automatic segmentation of the liver from CT scans. True 3D interaction with haptic feedback is used to facilitate initialization, i.e., seeding of a fast marching algorithm. Four users initialized 52 datasets and the mean interaction time was 40 seconds. The segmentation accuracy was verified by a radiologist. Volume measurements and segmentation precision show that the method has a high reproducibility.
PubMed: 17354843
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pubmed:17354843Le document en format XML
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International Conference on Medical Image Computing and Computer-Assisted Intervention</title><imprint><date when="2006" type="published">2006</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Artificial Intelligence</term><term>Computer Simulation</term><term>Hepatectomy (methods)</term><term>Humans</term><term>Imaging, Three-Dimensional (methods)</term><term>Liver (radiography)</term><term>Liver (surgery)</term><term>Models, Biological</term><term>Pattern Recognition, Automated (methods)</term><term>Radiographic Image Enhancement (methods)</term><term>Radiographic Image Interpretation, Computer-Assisted (methods)</term><term>Reproducibility of Results</term><term>Sensitivity and Specificity</term><term>Surgery, Computer-Assisted (methods)</term><term>Touch</term><term>User-Computer Interface</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Hepatectomy</term><term>Imaging, Three-Dimensional</term><term>Pattern Recognition, Automated</term><term>Radiographic Image Enhancement</term><term>Radiographic Image Interpretation, Computer-Assisted</term><term>Surgery, Computer-Assisted</term></keywords><keywords scheme="MESH" qualifier="radiography" xml:lang="en"><term>Liver</term></keywords><keywords scheme="MESH" qualifier="surgery" xml:lang="en"><term>Liver</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Artificial Intelligence</term><term>Computer Simulation</term><term>Humans</term><term>Models, Biological</term><term>Reproducibility of Results</term><term>Sensitivity and Specificity</term><term>Touch</term><term>User-Computer Interface</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">We present a method for semi-automatic segmentation of the liver from CT scans. True 3D interaction with haptic feedback is used to facilitate initialization, i.e., seeding of a fast marching algorithm. Four users initialized 52 datasets and the mean interaction time was 40 seconds. The segmentation accuracy was verified by a radiologist. Volume measurements and segmentation precision show that the method has a high reproducibility.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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