Artjoms Suponenkovs 1, Ardis Platkajis 2, Zigurds Markovics 1
1Faculty of computer science and information technology, Riga Technical University, Riga, Latvia
2Medical Academy of Latvia, Riga, Latvia
Introduction: There is a growth in the number of people with osteoarthritis. Consequently, the analysis of knee articular cartilage degeneration by magnetic resonance imaging data is very important. The magnetic resonance imaging data of a knee contains a lot of information. Unfortunately, a radiology technologist who uses simple (grayscale) images can analyze only a small part of knee data. The aim of the proposed methods is to provide more information about knee articular cartilage.
Materials and Methods: This paper proposes methods for visualization of knee cartilage, segmentation of knee tissues and analysis of cartilage changes.
Results: The experimental part contains the results and descriptions of visualization, segmentation and analysis methods.
Conclusions: The proposed methods and data obtained from cartilage experiments can be useful for diagnosing osteoarthritis, which will allow starting treatment earlier and therefore reducing the risk of cartilage destruction.
Keyword: medical imaging; knee-joint; computer vision; osteoarthritis; image pre-processing; magnetic resonance imaging; image segmentation; tissue analysis; DICOM.