Literature DB >> 16464631

Segmentation of volumetric MRA images by using capillary active contour.

Pingkun Yan1, Ashraf A Kassim.   

Abstract

Precise segmentation of three-dimensional (3D) magnetic resonance angiography (MRA) images can be a very useful computer aided diagnosis (CAD) tool for clinical routines. Level sets based evolution schemes, which have been shown to be effective and easy to implement for many segmentation applications, are being applied to MRA data sets. In this paper, we present a segmentation scheme for accurately extracting vasculature from MRA images. Our proposed algorithm models capillary action and derives a capillary active contour for segmentation of thin vessels. The algorithm is implemented using the level set method and has been applied successfully on real 3D MRA images. Compared with other state-of-the-art MRA segmentation algorithms, experiments show that our method facilitates more accurate segmentation of thin blood vessels.

Mesh:

Year:  2006        PMID: 16464631     DOI: 10.1016/j.media.2005.12.002

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  11 in total

1.  A fast and fully automatic method for cerebrovascular segmentation on time-of-flight (TOF) MRA image.

Authors:  Xin Gao; Yoshikazu Uchiyama; Xiangrong Zhou; Takeshi Hara; Takahiko Asano; Hiroshi Fujita
Journal:  J Digit Imaging       Date:  2011-08       Impact factor: 4.056

2.  A non-parametric vessel detection method for complex vascular structures.

Authors:  Xiaoning Qian; Matthew P Brennan; Donald P Dione; Wawrzyniec L Dobrucki; Marcel P Jackowski; Christopher K Breuer; Albert J Sinusas; Xenophon Papademetris
Journal:  Med Image Anal       Date:  2008-06-14       Impact factor: 8.545

3.  A 3D model of human cerebrovasculature derived from 3T magnetic resonance angiography.

Authors:  Wieslaw L Nowinski; Ihar Volkau; Yevgen Marchenko; A Thirunavuukarasuu; Ting Ting Ng; Val M Runge
Journal:  Neuroinformatics       Date:  2008-11-18

4.  Adaptive segmentation of cerebrovascular tree in time-of-flight magnetic resonance angiography.

Authors:  J T Hao; M L Li; F L Tang
Journal:  Med Biol Eng Comput       Date:  2007-09-06       Impact factor: 2.602

5.  Development of a quantitative intracranial vascular features extraction tool on 3D MRA using semiautomated open-curve active contour vessel tracing.

Authors:  Li Chen; Mahmud Mossa-Basha; Niranjan Balu; Gador Canton; Jie Sun; Kristi Pimentel; Thomas S Hatsukami; Jenq-Neng Hwang; Chun Yuan
Journal:  Magn Reson Med       Date:  2017-10-17       Impact factor: 4.668

6.  A novel method for identifying a graph-based representation of 3-D microvascular networks from fluorescence microscopy image stacks.

Authors:  Sepideh Almasi; Xiaoyin Xu; Ayal Ben-Zvi; Baptiste Lacoste; Chenghua Gu; Eric L Miller
Journal:  Med Image Anal       Date:  2014-11-28       Impact factor: 8.545

7.  Joint volumetric extraction and enhancement of vasculature from low-SNR 3-D fluorescence microscopy images.

Authors:  Sepideh Almasi; Ayal Ben-Zvi; Baptiste Lacoste; Chenghua Gu; Eric L Miller; Xiaoyin Xu
Journal:  Pattern Recognit       Date:  2016-09-22       Impact factor: 7.740

8.  3D vasculature segmentation using localized hybrid level-set method.

Authors:  Qingqi Hong; Qingde Li; Beizhan Wang; Yan Li; Junfeng Yao; Kunhong Liu; Qingqiang Wu
Journal:  Biomed Eng Online       Date:  2014-12-16       Impact factor: 2.819

9.  A vessel active contour model for vascular segmentation.

Authors:  Yun Tian; Qingli Chen; Wei Wang; Yu Peng; Qingjun Wang; Fuqing Duan; Zhongke Wu; Mingquan Zhou
Journal:  Biomed Res Int       Date:  2014-07-01       Impact factor: 3.411

10.  A vessel segmentation method for multi-modality angiographic images based on multi-scale filtering and statistical models.

Authors:  Pei Lu; Jun Xia; Zhicheng Li; Jing Xiong; Jian Yang; Shoujun Zhou; Lei Wang; Mingyang Chen; Cheng Wang
Journal:  Biomed Eng Online       Date:  2016-11-08       Impact factor: 2.819

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