الصفحة 1
الصفحة 1
La gonarthrose : Traitement chirurgical : De l´arthroscopie à la prothèse = Knee osteoarthritis : Surgical treatment : from arthroscopy to prosthesis
The aim of this work is to take stock in a clear and didactic way on all the current knowledge on osteoarthritis of the knee and its treatment. It successively addresses the diagnosis and the medical treatment, then the surgical treatments then finally the various aspects of the total knee prosthesis. This book is designed to be read at several levels: basic information is intended particularly for non-specialist or trainee surgeons, rheumatologists, rehabilitation physicians, radiologists and physiotherapists. More specialized aspects are discussed in a second part of the book concerning the future of medical treatment (biology, gene therapy) and certain complex problems of surgical techniques. The points of controversy concerning the total knee replacement are discussed in the last part of the book, of interest to physicians and surgeons.
3D Segmentation for medical images (OsteoVision) = التقطيع ثلاثي الأبعاد للصور الطبية
With the increasing integration of AI across various sectors, artificial intelligence (AI) is already playing a significant role in the healthcare industry, and its use is expected to grow further. AI systems used in image processing and computer vision algorithms have shown a significant ability to perform many operations such as segmentation, classification, and detection. This project presents the application of computer vision algorithms in the field of medical imaging for diagnostic, therapeutic, and interventional purposes. This thesis explores the use of several computer vision algorithms to address different pathologies, specifically brain tumors (glioma) (see Appendix A) and knee osteoarthritis (OA), as well as tracking the progression of knee osteoarthritis using the Kellgren and Lawrence (KL) grading system, a common method for classifying the severity of OA into five grades. To achieve the desired impact, the project employs various techniques, including 3D segmentation for brain tumors, 2D segmentation for knee joints, and multinomial classification for determining the severity of knee OA injuries. The primary aims of the project are to enhance diagnostic accuracy, assist in creating treatment plans, provide an assistive tool for healthcare providers to make more informed decisions, leverage AI's capabilities to detect abnormalities that might escape the human eye, and streamline workflow. To facilitate these goals, the project incorporates a user-friendly UI, a website, and a Flutter-based mobile application, enabling healthcare providers to efficiently integrate these tools into their practice and improve patient care.
