الصفحة 1
الصفحة 1
High-Grade Gliomas : Diagnosis and Treatment
This is truly an exciting time in the field of neuro-oncology, particularly in the area of hi- grade gliomas. The management of patients with high-grade gliomas has historically been one of the most challenging and disheartening fields in medicine, where failure is the rule and longevity is the exception. The jaded often state that despite purported advances in surgical and radiotherapeutic techniques and a myriad of clinical trials of medical therapies, the s- vival statistics for glioblastoma have not changed in the last three decades. The nihilism associated with these tumors is such that some practitioners still advise against treatment or even biopsy, recommending palliative care with the diagnosis based only on history and an MRI scan. If the current state-of-the-art in the diagnosis and management of high-grade gliomas was truly so bleak, there would be no reason to compile and publish a monograph on the subject. The fact is that we have recently entered an era where real progress is being made in our understanding and treatment of high-grade gliomas that is directly benefiting some patients. We are slowly but surely chipping away at this problem. One approach has exploited correlations between particular molecular markers and therapeutic response.
Advances and technical standards in neurosurgery : Vol. 32
This volume of Advances and Technical Standards in Neurosurgery covers some important new developments in functional neurosurgery and endovascular therapy. In the Technical Standards section a variety of topics are considered, including optic pathway gliomas, pineal lesions, cavernous sinus meningiomas, and the eternal problem of minor and repetitive head injury. Endovascular treatment of a variety of lesions is now common practice, and the state of the art in endovascular treatment for acute ischemic stroke is reviewed. An appraisal of the evidence on whether there is a place for microsurgical vascular decompression for essential hypertension raises interesting questions.
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.
