DocumentCode :
184477
Title :
Automatic prostate segmentation from transrectal ultrasound images
Author :
Yanyan Yu ; Jieyu Cheng ; Jizhou Li ; Weifu Chen ; Chiu, Bernard
Author_Institution :
Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong, China
fYear :
2014
fDate :
22-24 Oct. 2014
Firstpage :
117
Lastpage :
120
Abstract :
In this paper, a fully automatic slice-based 3D segmentation method is proposed to segment the sequence of the TRUS prostate images. The initial contour was generated on an initial frame of a stack of 2D ultrasound images acquired for each subject. This initial frame and the initial prostate boundary on this frame were automatically determined based on the radial bas-relief method. Then a region-based level set framework was applied to deform the initial contour using the approximate and detailed coefficients generated using dyadic wavelet transform. Finally, the segmented contour on initial frame is propagated to the adjacent frames as initial contour until all the frames are segmented. 50 transverse prostate images from three patients were segmented using the proposed algorithm for validation. The average mean absolute difference (MAD) between the contour segmented using the proposed algorithm and the manually outlined contour is less than 5 pixels.
Keywords :
biomedical ultrasonics; image segmentation; image sequences; medical image processing; wavelet transforms; 2D ultrasound image acquisition; MAD; TRUS prostate image sequence; automatic prostate segmentation; automatic slice-based 3D segmentation; contour segmentation; deformation; dyadic transform; mean absolute difference; prostate boundary; radial bas-relief method; region-based level set framework; transrectal ultrasound images; transverse prostate images; Image segmentation; Integrated circuits; Transforms; dyadic wavelet transform; level set framework; transrectal ultrasound image;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Circuits and Systems Conference (BioCAS), 2014 IEEE
Conference_Location :
Lausanne
Type :
conf
DOI :
10.1109/BioCAS.2014.6981659
Filename :
6981659
Link To Document :
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