Knee Meniscus Segmentation and Tear Detection from MRI: A Review - Saygili, Ahmet; Albayrak, Songul (BENTHAM SCIENCE PUBL LTD, 2020)
Background: Automatic diagnostic systems in medical imaging provide useful information to support radiologists and other relevant experts. The systems that help radiologists in their analysis and diagnosis appear to be increasing. Discussion: Knee joints are intensively studied structures, as well. In this review, studies that automatically segment meniscal structures from the knee joint MR images and detect tears have been investigated. Some of the studies in the literature merely perform meniscus segmentation, while others include classification procedures that detect both meniscus segmentation and anomalies on menisci. The studies performed on the meniscus were categorized according to the methods they used. The methods used and the results obtained from such studies were analyzed along with their drawbacks, and the aspects to be developed were also emphasized. Conclusion: The work that has been done in this area can effectively support the decisions that will be made by radiology and orthopedics specialists. Furthermore, these operations, which were performed manually on MR images, can be performed in a shorter time with the help of computer-aided systems, which enables early diagnosis and treatment.
Keywords: Knee joint; CAD; segmentation; meniscus; tear detection; MRI; medical image; BRAIN-TUMOR SEGMENTATION; MAGNETIC-RESONANCE IMAGES; BREAST-CANCER DETECTION; MARKOV RANDOM-FIELD; REGION-GROWING ALGORITHM; AUTOMATED SEGMENTATION; BONE SEGMENTATION; NEURAL-NETWORKS; CARTILAGE; CLASSIFICATION; Radiology, Nuclear Medicine & Medical Imaging