Thickness mapping techniques are important in the management of osteoarthritis. Since most thickness mapping approaches require two surfaces as inputs, surface segmentation is important for articular cartilage thickness mapping. In this work, a systematic approach is proposed for automatic articular cartilage surface segmentation from a volume segmentation mask, which includes cartilage surface reconstruction, body surface construction, surface normal estimation, directional voxels searching, restricted surface dilation, and surface close operation. The proposed method can be used for reliable cartilage thickness mapping.
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