NDLI: Automatic liver segmentation from CT images using latent semantic indexing

Content Provider	IEEE Xplore Digital Library
Author	Chun-Yao Hsieh Shyi-Chyi Cheng Chin-Chun Chang Chin-Lang Lin
Copyright Year	2015
Description	Author affiliation: Liver Res. Unit, Chang Gung Memorial Hosp., Keelung, Taiwan (Chin-Lang Lin) \|\| Dept. of Comput. Sci. & Eng., Nat. Taiwan Ocean Univ., Keelung, Taiwan (Chun-Yao Hsieh; Shyi-Chyi Cheng; Chin-Chun Chang)
Abstract	In this paper, we present an indexing structure of data-driven cuboid patterns to speed up the process of liver detection and segmentation from computed tomography (CT) scans using the cube-based generalized Hough transform (CGHT). Most existing approaches to automatic liver segmentation from CT scans use a statistical shape model (SSM) integrated with a searching algorithm to recover the deformation. However, establishing the correspondences among landmark points of training shapes for the construction of the average shape of SSM remains as a challenge due to the high variation of liver shapes in CT scans. The proposed method is a fully automatic segmentation method that combines four steps. Firstly, a test CT volume is partitioned into multiple non-overlapped sub-volumes with each of them consisting of variable numbers of consecutive slices. Secondly, we locate the cube-based liver shapes in all sub-volumes via Hough voting and dynamic programming. Thirdly, we construct the basic 3D model through a level-set framework for liver shape segmentation. Finally, to introduce neighbors statistical analysis into the above model, we deform the 3D liver shape to overcome disturbances caused by noise and inhomogeneity. The MICCAI 2007 liver segmentation challenge datasets are used to verify the effectiveness of the proposed method. Experimental results demonstrate the good performance of the proposed method in terms of segmentation accuracy and execution speed.
Starting Page	1
Ending Page	6
File Size	1055557
Page Count	6
File Format	PDF
e-ISBN	9781467374781
DOI	10.1109/MMSP.2015.7340801
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Liver Computed tomography Shape Three-dimensional displays Training Image segmentation Solid modeling
Content Type	Text
Resource Type	Article

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