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Proceedings Paper

Medical image segmentation using 3D MRI data
Author(s): V. Voronin; V. Marchuk; E. Semenishchev; Yigang Cen; S. Agaian
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Paper Abstract

Precise segmentation of three-dimensional (3D) magnetic resonance imaging (MRI) image can be a very useful computer aided diagnosis (CAD) tool in clinical routines. Accurate automatic extraction a 3D component from images obtained by magnetic resonance imaging (MRI) is a challenging segmentation problem due to the small size objects of interest (e.g., blood vessels, bones) in each 2D MRA slice and complex surrounding anatomical structures. Our objective is to develop a specific segmentation scheme for accurately extracting parts of bones from MRI images. In this paper, we use a segmentation algorithm to extract the parts of bones from Magnetic Resonance Imaging (MRI) data sets based on modified active contour method. As a result, the proposed method demonstrates good accuracy in a comparison between the existing segmentation approaches on real MRI data.

Paper Details

Date Published: 10 May 2017
PDF: 8 pages
Proc. SPIE 10221, Mobile Multimedia/Image Processing, Security, and Applications 2017, 102210A (10 May 2017); doi: 10.1117/12.2262857
Show Author Affiliations
V. Voronin, Don State Technical Univ. (Russian Federation)
V. Marchuk, Don State Technical Univ. (Russian Federation)
E. Semenishchev, Don State Technical Univ. (Russian Federation)
Yigang Cen, Beijing Jiaotong Univ. (China)
S. Agaian, The Univ. of Texas at San Antonio (United States)

Published in SPIE Proceedings Vol. 10221:
Mobile Multimedia/Image Processing, Security, and Applications 2017
Sos S. Agaian; Sabah A. Jassim, Editor(s)

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