Automated 3D Surface Display for Evaluating Meniscal Tears Aided by Fuzzy Expert System

This paper proposes an automated procedure for segmenting menisci in MR images of a human knee aided by fuzzy expert system. A three-dimensional (3D) MR volumetric images composed of many slice images consists of several parts: bone marrow, meniscus, periarticular liquor, cartilage and others. We employ both T1-weighted and T2-weighted MR images to identify the menisci with high accuracy. After a registration between these images is manually done on a computer display, our procedure aided by fuzzy expert system can automatically segment meniscal regions from 3D MR images. Physicians can observe the 3D shapes of meniscal tears from any point of view on the display. We examined five subjects including a normal knee and three injured knees. The all meniscal regions were significantly identified, and these 3D shapes were displayed. The patterns of meniscal tears were identified on the display for all subjects. In a subject, since the preoperative and postoperative 3D meniscal shapes were clearly viewed, we easily recognized the operated meniscal regions. Thus, the system can provide useful information for diagnosing meniscal tears.