Medical image series segmentation using watershed transform and active contour model
In this paper, a semiautomatic algorithm based on the combination of the live wire algorithm and the active contour model is proposed for the segmentation of medical image series. First we obtain accurate segmentation of one or more slices in a medical image series by combining the livewire algorith...
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creator | Fu-Ping Zhu Jie Tian Xi-Ping Luo Xing-Fei Ge |
description | In this paper, a semiautomatic algorithm based on the combination of the live wire algorithm and the active contour model is proposed for the segmentation of medical image series. First we obtain accurate segmentation of one or more slices in a medical image series by combining the livewire algorithm with the watershed method. Then the computer will segment the nearby slice using the modified active contour model. We introduce a gray-scale model to the boundary points of the active contour model to record the local region characters of the desired object in the segmented slice and replace the external energy of the traditional active contour model with the energy decided by the likelihood of the grayscale model. Moreover we introduce the active region concept of the snake to improve the segmentation accuracy. Experiment shows. that our algorithm can obtain the boundary of the desired object from a series of medical images reliably with only little user intervention. |
doi_str_mv | 10.1109/ICMLC.2002.1174506 |
format | Conference Proceeding |
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International Conference on Machine Learning and Cybernetics</title><addtitle>ICMLC</addtitle><description>In this paper, a semiautomatic algorithm based on the combination of the live wire algorithm and the active contour model is proposed for the segmentation of medical image series. First we obtain accurate segmentation of one or more slices in a medical image series by combining the livewire algorithm with the watershed method. Then the computer will segment the nearby slice using the modified active contour model. We introduce a gray-scale model to the boundary points of the active contour model to record the local region characters of the desired object in the segmented slice and replace the external energy of the traditional active contour model with the energy decided by the likelihood of the grayscale model. Moreover we introduce the active region concept of the snake to improve the segmentation accuracy. Experiment shows. that our algorithm can obtain the boundary of the desired object from a series of medical images reliably with only little user intervention.</description><subject>Active contours</subject><subject>Artificial intelligence</subject><subject>Automation</subject><subject>Biomedical imaging</subject><subject>Computer vision</subject><subject>Electronic mail</subject><subject>Gray-scale</subject><subject>Image analysis</subject><subject>Image segmentation</subject><subject>Wire</subject><isbn>9780780375086</isbn><isbn>0780375084</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2002</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj91KAzEUhAMiKLUvoDd5ga0nm02yeymLP4WW3tTrcnZzskb2R5JU8e0N2GGGYW4GPsbuBWyEgOZx2-537aYEKPM2lQJ9xdaNqSFbGgW1vmHrGD8hq6qUlOqWHfdkfY8j9xMOxCMFTzHXMNGcMPll5ufo54H_YKIQP8jyFHCObgkTx9ly7JP_Jt4vc1rOgU-LpfGOXTscI60vvWLvL8_H9q3YHV637dOu8MLIVKDrVI9G6KbToExVu1JIJW1tHXZgUTsNojTQkFAodJ9R6hKEcrXrpclZsYf_X09Ep6-QGcLv6cIu_wA10VBq</recordid><startdate>2002</startdate><enddate>2002</enddate><creator>Fu-Ping Zhu</creator><creator>Jie Tian</creator><creator>Xi-Ping Luo</creator><creator>Xing-Fei Ge</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>2002</creationdate><title>Medical image series segmentation using watershed transform and active contour model</title><author>Fu-Ping Zhu ; Jie Tian ; Xi-Ping Luo ; Xing-Fei Ge</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i173t-afb5ca7169b605748f21353d8dfab0da6f6012709e15a16c97882015f8fc37fc3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Active contours</topic><topic>Artificial intelligence</topic><topic>Automation</topic><topic>Biomedical imaging</topic><topic>Computer vision</topic><topic>Electronic mail</topic><topic>Gray-scale</topic><topic>Image analysis</topic><topic>Image segmentation</topic><topic>Wire</topic><toplevel>online_resources</toplevel><creatorcontrib>Fu-Ping Zhu</creatorcontrib><creatorcontrib>Jie Tian</creatorcontrib><creatorcontrib>Xi-Ping Luo</creatorcontrib><creatorcontrib>Xing-Fei Ge</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Fu-Ping Zhu</au><au>Jie Tian</au><au>Xi-Ping Luo</au><au>Xing-Fei Ge</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Medical image series segmentation using watershed transform and active contour model</atitle><btitle>Proceedings. International Conference on Machine Learning and Cybernetics</btitle><stitle>ICMLC</stitle><date>2002</date><risdate>2002</risdate><volume>2</volume><spage>865</spage><epage>870 vol.2</epage><pages>865-870 vol.2</pages><isbn>9780780375086</isbn><isbn>0780375084</isbn><abstract>In this paper, a semiautomatic algorithm based on the combination of the live wire algorithm and the active contour model is proposed for the segmentation of medical image series. First we obtain accurate segmentation of one or more slices in a medical image series by combining the livewire algorithm with the watershed method. Then the computer will segment the nearby slice using the modified active contour model. We introduce a gray-scale model to the boundary points of the active contour model to record the local region characters of the desired object in the segmented slice and replace the external energy of the traditional active contour model with the energy decided by the likelihood of the grayscale model. Moreover we introduce the active region concept of the snake to improve the segmentation accuracy. Experiment shows. that our algorithm can obtain the boundary of the desired object from a series of medical images reliably with only little user intervention.</abstract><pub>IEEE</pub><doi>10.1109/ICMLC.2002.1174506</doi></addata></record> |
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subjects | Active contours Artificial intelligence Automation Biomedical imaging Computer vision Electronic mail Gray-scale Image analysis Image segmentation Wire |
title | Medical image series segmentation using watershed transform and active contour model |
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