Cerebral Circulation

Diagnostics and diseases related to the cerebrovascular system are constantly evolving and updating. 3D augmented reality or quantification of cerebral perfusion are becoming important diagnostic tools in daily practice and the role of the cerebral venous system is being constantly revised considering new theories such as that of “the glymphatic system.” This book provides updates on models, diagnosis, and treatment of diseases of the cerebrovascular system

Diseases of the Brain, Head and Neck, Spine 2020–2023

This open access book offers an essential overview of brain, head and neck, and spine imaging. Over the last few years, there have been considerable advances in this area, driven by both clinical and technological developments. Written by leading international experts and teachers, the chapters are disease-oriented and cover all relevant imaging modalities, with a focus on magnetic resonance imaging and computed tomography. The book also includes a synopsis of pediatric imaging. IDKD books are rewritten (not merely updated) every four years, which means they offer a comprehensive review of the state-of-the-art in imaging. The book is clearly structured and features learning objectives, abstracts, subheadings, tables and take-home points, supported by design elements to help readers navigate the text. It will particularly appeal to general radiologists, radiology residents, and interventional radiologists who want to update their diagnostic expertise, as well as clinicians from other specialties who are interested in imaging for their patient care

Application of emerging technologies in ischemic stroke: from clinical study to basic research

Stroke is a primary cause of noncommunicable disease-related death and disability worldwide. The most common form, ischemic stroke, is increasing in incidence resulting in a significant burden on patients and society. Urgent action is thus needed to address preventable risk factors and improve treatment methods. This review examines emerging technologies used in the management of ischemic stroke, including neuroimaging, regenerative medicine, biology, and nanomedicine, highlighting their benefits, clinical applications, and limitations. Additionally, we suggest strategies for technological development for the prevention, diagnosis, and treatment of ischemic stroke

Neurovascular Surgery

This open access book presents the diagnosis, investigation and treatment of neurovascular diseases, and offers expert opinions and advice on avoiding complications in neurovascular surgery. It also covers complication management and post-operative follow-up care. The book is divided in to three parts; the first part discusses common approaches in neurovascular surgery, describing the steps, indications for and limitations of the approach, as well as the associated complications and how to avoid them. The second part addresses surgical treatment based on pathology, taking the different locations of lesions into consideration. The third part focuses on the technological developments that support neurovascular surgery, which may not be available everywhere, but have been included to help vascular surgeon understand the principles. This book is a guide for young neurosurgeons, neurosurgery residents and neurosurgery fellows, as well as for medical students and nurses who are interested in neurosurgery or are associated with this field in any way. It is also a useful teaching aid for senior neurosurgeons

CAD system for early diagnosis of diabetic retinopathy based on 3D extracted imaging markers.

This dissertation makes significant contributions to the field of ophthalmology, addressing the segmentation of retinal layers and the diagnosis of diabetic retinopathy (DR). The first contribution is a novel 3D segmentation approach that leverages the patientspecific anatomy of retinal layers. This approach demonstrates superior accuracy in segmenting all retinal layers from a 3D retinal image compared to current state-of-the-art methods. It also offers enhanced speed, enabling potential clinical applications. The proposed segmentation approach holds great potential for supporting surgical planning and guidance in retinal procedures such as retinal detachment repair or macular hole closure. Surgeons can benefit from the accurate delineation of retinal layers, enabling better understanding of the anatomical structure and more effective surgical interventions. Moreover, real-time guidance systems can be developed to assist surgeons during procedures, improving overall patient outcomes. The second contribution of this dissertation is the introduction of a novel computeraided diagnosis (CAD) system for precise identification of diabetic retinopathy. The CAD system utilizes 3D-OCT imaging and employs an innovative approach that extracts two distinct features: first-order reflectivity and 3D thickness. These features are then fused and used to train and test a neural network classifier. The proposed CAD system exhibits promising results, surpassing other machine learning and deep learning algorithms commonly employed in DR detection. This demonstrates the effectiveness of the comprehensive analysis approach employed by the CAD system, which considers both low-level and high-level data from the 3D retinal layers. The CAD system presents a groundbreaking contribution to the field, as it goes beyond conventional methods, optimizing backpropagated neural networks to integrate multiple levels of information effectively. By achieving superior performance, the proposed CAD system showcases its potential in accurately diagnosing DR and aiding in the prevention of vision loss. In conclusion, this dissertation presents novel approaches for the segmentation of retinal layers and the diagnosis of diabetic retinopathy. The proposed methods exhibit significant improvements in accuracy, speed, and performance compared to existing techniques, opening new avenues for clinical applications and advancements in the field of ophthalmology. By addressing future research directions, such as testing on larger datasets, exploring alternative algorithms, and incorporating user feedback, the proposed methods can be further refined and developed into robust, accurate, and clinically valuable tools for diagnosing and monitoring retinal diseases