Sparse patch based prostate segmentation in CT images.

Shu Liao, Yaozong Gao, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingChapter

18 Citations (Scopus)

Abstract

Automatic prostate segmentation plays an important role in image guided radiation therapy. However, accurate prostate segmentation in CT images remains as a challenging problem mainly due to three issues: Low image contrast, large prostate motions, and image appearance variations caused by bowel gas. In this paper, a new patient-specific prostate segmentation method is proposed to address these three issues. The main contributions of our method lie in the following aspects: (1) A new patch based representation is designed in the discriminative feature space to effectively distinguish voxels belonging to the prostate and non-prostate regions. (2) The new patch based representation is integrated with a new sparse label propagation framework to segment the prostate, where candidate voxels with low patch similarity can be effectively removed based on sparse representation. (3) An online update mechanism is adopted to capture more patient-specific information from treatment images scanned in previous treatment days. The proposed method has been extensively evaluated on a prostate CT image dataset consisting of 24 patients with 330 images in total. It is also compared with several state-of-the-art prostate segmentation approaches, and experimental results demonstrate that our proposed method can achieve higher segmentation accuracy than other methods under comparison.

Original languageEnglish
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Pages385-392
Number of pages8
Volume15
EditionPt 3
Publication statusPublished - 2012 Dec 1

Fingerprint

Prostate
Image-Guided Radiotherapy
Gases
Therapeutics

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Liao, S., Gao, Y., & Shen, D. (2012). Sparse patch based prostate segmentation in CT images. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention (Pt 3 ed., Vol. 15, pp. 385-392)

Sparse patch based prostate segmentation in CT images. / Liao, Shu; Gao, Yaozong; Shen, Dinggang.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 15 Pt 3. ed. 2012. p. 385-392.

Research output: Chapter in Book/Report/Conference proceedingChapter

Liao, S, Gao, Y & Shen, D 2012, Sparse patch based prostate segmentation in CT images. in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 3 edn, vol. 15, pp. 385-392.
Liao S, Gao Y, Shen D. Sparse patch based prostate segmentation in CT images. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 3 ed. Vol. 15. 2012. p. 385-392
Liao, Shu ; Gao, Yaozong ; Shen, Dinggang. / Sparse patch based prostate segmentation in CT images. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 15 Pt 3. ed. 2012. pp. 385-392
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