Quantitative measurement and analysis for detection and treatment planning of developmental dysplasia of the hip

Xin Liu; Hongbing Lu; Hanyong Chen; Li Zhao; Zhengxing Shi; Zhengrong Liang

doi:10.1117/12.811531

27 February 2009 Quantitative measurement and analysis for detection and treatment planning of developmental dysplasia of the hip

Xin Liu, Hongbing Lu, Hanyong Chen, Li Zhao, Zhengxing Shi, Zhengrong Liang

Author Affiliations +

Proceedings Volume 7260, Medical Imaging 2009: Computer-Aided Diagnosis; 72603N (2009) https://doi.org/10.1117/12.811531
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Developmental dysplasia of the hip is a congenital hip joint malformation affecting the proximal femurs and acetabulum that are subluxatable, dislocatable, and dislocated. Conventionally, physicians made diagnoses and treatments only based on findings from two-dimensional (2D) images by manually calculating clinic parameters. However, anatomical complexity of the disease and the limitation of current standard procedures make accurate diagnosis quite difficultly. In this study, we developed a system that provides quantitative measurement of 3D clinical indexes based on computed tomography (CT) images. To extract bone structure from surrounding tissues more accurately, the system firstly segments the bone using a knowledge-based fuzzy clustering method, which is formulated by modifying the objective function of the standard fuzzy c-means algorithm with additive adaptation penalty. The second part of the system calculates automatically the clinical indexes, which are extended from 2D to 3D for accurate description of spatial relationship between femurs and acetabulum. To evaluate the system performance, experimental study based on 22 patients with unilateral or bilateral affected hip was performed. The results of 3D acetabulum index (AI) automatically provided by the system were validated by comparison with 2D results measured by surgeons manually. The correlation between the two results was found to be 0.622 (p<0.01).

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Xin Liu, Hongbing Lu, Hanyong Chen, Li Zhao, Zhengxing Shi, and Zhengrong Liang "Quantitative measurement and analysis for detection and treatment planning of developmental dysplasia of the hip", Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72603N (27 February 2009); https://doi.org/10.1117/12.811531

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KEYWORDS

3D metrology

Artificial intelligence

Bone

Image segmentation

3D image processing

Expectation maximization algorithms

Fuzzy logic

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