Segmentation of the hip articular cartilages is clinically important. In this research, we propose a multi-step method for automatic segmentation of the hip femoral cartilage from CT images. Differentiation of the acetabular and femoral cartilages in conventional CT images due to very narrow space and low intensity of the articular space is very difficult. For this reason, MRI of the hip under continuous leg traction is the choice for assessment of the hip articular cartilage. However, this procedure is time consuming, painful, and hence inconvenient. By injecting the contrast media in the hip during data acquisition, we separated the femoral and acetabular cartilage from each other. The multi-step approach for segmentation of the femoral cartilage is as follows. We first enhance the dynamic range and contrast of the data set by a conventional procedure. We then estimate the center of the femoral head utilizing a Hough transform. The estimated center is used as a pivotal point for beginning the process. Next, based on anatomical knowledge about the femoral head shape and size, we derive a region of interest (ROI) for further operations. In the acquired CT images, the hip cartilages are surrounding by high intensity contrast agents, pelvic and femoral bones. In this case, by employing an Image Bottom Hat technique and anatomical knowledge about the curved shaped of the cartilages, we extract the valleys between contrast media and hip bones. The valley between the contrast media and femoral head is associated with the femoral cartilage. The anatomical assumptions we applied in this research is valid in most hip joint images. The proposed model is successfully applied to eight sets (2816 images) of actual in vivo hip CT data.
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