MASCG: Multi-Atlas Segmentation Constrained Graph method for accurate segmentation of hip CT images

Chu, Chengwen; Bai, Junjie; Wu, Xiaodong; Zheng, Guoyan (2015). MASCG: Multi-Atlas Segmentation Constrained Graph method for accurate segmentation of hip CT images. Medical image analysis, 26(1), pp. 173-184. Elsevier 10.1016/j.media.2015.08.011

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This paper addresses the issue of fully automatic segmentation of a hip CT image with the goal to preserve the joint structure for clinical applications in hip disease diagnosis and treatment. For this purpose, we propose a Multi-Atlas Segmentation Constrained Graph (MASCG) method. The MASCG method uses multi-atlas based mesh fusion results to initialize a bone sheetness based multi-label graph cut for an accurate hip CT segmentation which has the inherent advantage of automatic separation of the pelvic region from the bilateral proximal femoral regions. We then introduce a graph cut constrained graph search algorithm to further improve the segmentation accuracy around the bilateral hip joint regions. Taking manual segmentation as the ground truth, we evaluated the present approach on 30 hip CT images (60 hips) with a 15-fold cross validation. When the present approach was compared to manual segmentation, an average surface distance error of 0.30 mm, 0.29 mm, and 0.30 mm was found for the pelvis, the left proximal femur, and the right proximal femur, respectively. A further look at the bilateral hip joint regions demonstrated an average surface distance error of 0.16 mm, 0.21 mm and 0.20 mm for the acetabulum, the left femoral head, and the right femoral head, respectively.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB [discontinued]

Graduate School:

Graduate School for Cellular and Biomedical Sciences (GCB)

UniBE Contributor:

Chu, Chengwen, Zheng, Guoyan

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISSN:

1361-8415

Publisher:

Elsevier

Language:

English

Submitter:

Li Liu

Date Deposited:

14 Mar 2016 16:40

Last Modified:

05 Dec 2022 14:52

Publisher DOI:

10.1016/j.media.2015.08.011

PubMed ID:

26426453

Uncontrolled Keywords:

CT; Graph cut; Graph search; Multi-atlas; Segmentation

BORIS DOI:

10.7892/boris.76876

URI:

https://boris.unibe.ch/id/eprint/76876

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