Segmenting the Femoral Head and Acetabulum in the Hip Joint Automatically Using a Multi-Step Scheme

Ji WANG  Yuanzhi CHENG  Yili FU  Shengjun ZHOU  Shinichi TAMURA  

IEICE TRANSACTIONS on Information and Systems   Vol.E95-D   No.4   pp.1142-1150
Publication Date: 2012/04/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E95.D.1142
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Biological Engineering
hip joint,  osteoarthritis,  mathematical morphology,  vertex normal,  threshold selection,  

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We describe a multi-step approach for automatic segmentation of the femoral head and the acetabulum in the hip joint from three dimensional (3D) CT images. Our segmentation method consists of the following steps: 1) construction of the valley-emphasized image by subtracting valleys from the original images; 2) initial segmentation of the bone regions by using conventional techniques including the initial threshold and binary morphological operations from the valley-emphasized image; 3) further segmentation of the bone regions by using the iterative adaptive classification with the initial segmentation result; 4) detection of the rough bone boundaries based on the segmented bone regions; 5) 3D reconstruction of the bone surface using the rough bone boundaries obtained in step 4) by a network of triangles; 6) correction of all vertices of the 3D bone surface based on the normal direction of vertices; 7) adjustment of the bone surface based on the corrected vertices. We evaluated our approach on 35 CT patient data sets. Our experimental results show that our segmentation algorithm is more accurate and robust against noise than other conventional approaches for automatic segmentation of the femoral head and the acetabulum. Average root-mean-square (RMS) distance from manual reference segmentations created by experienced users was approximately 0.68 mm (in-plane resolution of the CT data).