(untitled) (International Journal of Engineering and Computer Science, 2017)
Knee joint is the largest anatomical joint within the human body which facilitates the ease of movement from one place to another. Knees are most complex and delicate joints. Knee joints are frequently injured and damaged due to articulations. The knees are among the joints most commonly affected by osteoarthritis (OA). The pathophysiology of osteoarthritis (OA), a common debilitating disease afflicting over 71 million people globally, is poorly understood and a treatment to slow, halt, or reverse the disease progression remains elusive. Among the ligaments responsible in maintaining the structural integrity of knee joint, anterior cruciate ligament (ACL) injury is most commonly diagnosed. Recent advancement in clinical imaging technology has led to wide employment of magnetic resonance imaging (MRI) in such injury assessment. In this paper, a semiautomatic ACL Segmentation program implemented in MATLAB is proposed. It takes advantage of the ACL’s unique shape and orientation within MR images to carry out the segmentation. The goal of medical image segmentation is to partition a medical image in to separate regions, usually anatomic structures that are meaningful for a specific task. In many medical applications, such as diagnosis, surgery planning, and radiation treatm