Knee-joint tissue recognition in magnetic resonance imaging

The automatic knee-joint soft tissue recognition problem is very relevant due to increasing number of people with knee-joint diseases. It is for this reason that this paper investigates the problem of soft tissue recognition in magnetic resonance imaging (MRI). MRI is useful for knee-joint soft tissue presentation, but usually a doctor cannot see all necessary information in MRI data. Computer MRI analysis makes it possible to process all MRI data and shows additional information for the doctor. This additional information can make it easier to detect invisible injuries of knee-joint soft tissues. Knee-joint soft tissue recognition and analysis are very helpful, especially for osteoarthritis (OA) early diagnostics. Computer OA diagnostics are impossible without segmentation of knee-joint tissues. This publication describes approaches for knee-joint image pre-processing, knee-joint image segmentation, tissue recognition and tissue analysis. To solve tissue analysis task it is important to use biological information of knee-joint structure, physical and biochemical tissue features. Tissue analysis is very useful especially for early diagnostics. It allows starting treatment earlier and therefore reducing the risk of tissue destruction. It is for this reason that this paper investigates the above-mentioned challenges.