Download or read book Improving Acute Ischemic Stroke Diagnosis Using Medical Imaging and Deep Learning Methods written by Haoyue Zhang and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Acute ischemic stroke (AIS) is a cerebrovascular disease caused by deceased blood flow in the brain. Treatment of AIS is heavily dependent on the time since stroke onset (TSS), either by clock time or tissue time. AIS treatments aim to restore blood flow in the stroke-affected area to minimize infarction. Current clinical guidelines recommend thrombolytic therapies (e.g. Intravenous(IV) or Intra-arterial (IA) tissue Plasminogen Activator (tPA) for patients presenting within 4.5 hours of TSS and Mechanical Thrombectomy (MTB) (e.g. surgical removal of the clot) for patients with TSS up to 24 hours. This research attempts to use both CT and MRI to predict the eligibility of AIS patients and their response to treatment whileaddressing several challenges in neuroimaging and AIS diagnosis in clinical settings using novel machine learning and deep learning approaches. A Self-supervised Learning approach, called intra-domain task-adaptive transfer learning, is the first proposed to predict TSS using limited training data. A hybrid transformer model that utilizes spatial neighborhood information in brain regions is proposed to predict MTB success. A pure transformer and a specifically designed Masked Image Model are developed to predict Large Vessel Occlusion (LVO). Last, a transformer-based super-resolution framework is proposed to generate synthesized thin-slice images from thick-slice images. Together, these models demonstrate the effectiveness of the attention mechanism and the usefulness of self-supervised learning for clinical deep learning applications given the limited data resources compared to natural images.
Download or read book Improving Acute Ischemic Stroke Clinical and Imaging Outcome Classification Using Machine Learning and Deep Learning Methods written by King Chung Ho and published by . This book was released on 2019 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stroke is the fifth leading cause of death in the United States, with approximately 795,000 new cases each year. The goal of stroke treatment is to rescue salvageable tissue by reperfusion therapy. Clinical trials have shown that intravenous tissue plasminogen activator (IV tPA) and clot retrieval devices are effective treatments for recanalizing occluded blood vessels. However, determining an optimal stroke treatment plan is not a straightforward decision because it involves different factors, such as patient risk of hemorrhage and penumbra size. The relationships between these factors and patient outcomes are not clearly understood. This dissertation attempts to overcome these challenges by developing machine learning and deep learning models for acute ischemic stroke clinical and imaging outcome classification. A novel deep learning model was first proposed using source perfusion imaging to predict voxel-wise tissue outcome. The model architecture is designed to include contralateral patches to improve the feature learning process. Second, an end-to-end machine learning approach was developed to classify stroke onset time, which is a major clinical variable in selecting patients for IV tPA treatments. The approach combines baseline descriptive features and deep features to improve stroke onset time classification using machine learning models. Third, a bi-input convolutional neural network was developed for perfusion parameter estimation. This model lays a foundation to estimate perfusion parameters using pattern recognition techniques. Finally, a machine learning model trained with a balanced data set was developed for acute stroke patient outcome prediction. Rigorous experiments and results have shown the effectiveness of these proposed methods. This dissertation describes methods that lead to better understanding of stroke imaging, which lays the foundation to offer decision-making guidance for clinicians providing acute stroke intervention treatments.
Download or read book Machine Learning in Action Stroke Diagnosis and Outcome Prediction written by Ramin Zand and published by Frontiers Media SA. This book was released on 2022-08-18 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machine Learning and Deep Learning in Neuroimaging Data Analysis written by Anitha S. Pillai and published by CRC Press. This book was released on 2024-02-15 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning (ML) and deep learning (DL) have become essential tools in healthcare. They are capable of processing enormous amounts of data to find patterns and are also adopted into methods that manage and make sense of healthcare data, either electronic healthcare records or medical imagery. This book explores how ML/DL can assist neurologists in identifying, classifying or predicting neurological problems that require neuroimaging. With the ability to model high-dimensional datasets, supervised learning algorithms can help in relating brain images to behavioral or clinical observations and unsupervised learning can uncover hidden structures/patterns in images. Bringing together artificial intelligence (AI) experts as well as medical practitioners, these chapters cover the majority of neuro problems that use neuroimaging for diagnosis, along with case studies and directions for future research.
Download or read book Hemorrhagic and Ischemic Stroke written by Bernard R. Bendok and published by Thieme. This book was released on 2024-08-23 with total page 1368 pages. Available in PDF, EPUB and Kindle. Book excerpt: A transdisciplinary approach to the medical, radiologic, interventional, and surgical treatment of stroke In the last decade, advances in interventional, microsurgcial, radiosurgical techniques, medical approaches and imaging technology have dramatically changed the management of ischemic stroke. Perhaps the most important advance has been the increasing collaboration between multispecialty clinicians to deliver team-based stroke care. Hemorrhagic and Ischemic Stroke: Medical, Imaging, Surgical, and Interventional Approaches, Second Edition by renowned neurosurgeons Bernard R. Bendok and H. Hunt Batjer and acclaimed contributors provides a user-friendly, single resource for managing ischemic and hemorrhagic stroke. The second edition has been updated to reflect progress, most notably acute evaluation and triage, advanced imaging, critical care and medical support, and endovascular and surgical interventions. In addition to scientifically supported content, readers will benefit from pragmatic, real-world applications and concise, practical reviews. Organized into four sections and 41 chapters, the text starts with the section Acute Triage, which includes early diagnosis and medical decision-making, advances in medical imaging, innovations in prehospital management of stroke, and the promise of telestroke networks. The second section, Critical Care, covers the importance of astute clinical examination, stabilization, and advanced neuromonitoring techniques. The third section, Open Surgical, Minimally Invasive, and Microsurgical Approaches, reviews recent surgical innovations that have the potential to be lifesaving and enhance quality of life in select patients. The fourth and final section, Neurointerventional Approaches, explores recent innovations in image-guided catheter techniques to deliver new therapies for stroke treatment and prevention. Key Highlights The often difficult yet important adjudication of antithrombotic medication use Insightful discussion of the importance of prehospital systems of care and stroke center certification Insightful discussions of interventional and microsurgical approaches for hemorrhagic and ischemic stroke management Medical illustrations and author-narrated videos provide a visual learning experience Clinical pearls and case presentations enhance learning and retention of knowledge The goal of this book is to increase collaborative stroke management among neuroradiologists, neurologists, neurosurgeons, neuroanesthesiolgists, neurologic critical care physicians, and allied health care professionals to achieve better patient outcomes.
Download or read book Machine Learning and Decision Support in Stroke written by Fabien Scalzo and published by Frontiers Media SA. This book was released on 2020-07-09 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Acute Ischemic Stroke written by R. Gilberto González and published by Springer Science & Business Media. This book was released on 2010-10-05 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: This updated second edition of Acute Ischemic Stroke: Imaging and Intervention provides a comprehensive account of the state of the art in the diagnosis and treatment of acute ischemic stroke. The basic format of the first edition has been retained, with sections on fundamentals such as pathophysiology and causes, imaging techniques and interventions. However, each chapter has been revised to reflect the important recent progress in advanced neuroimaging and the use of interventional tools. In addition, a new chapter is included on the classification instruments for ischemic stroke and their use in predicting outcomes and therapeutic triage. All of the authors are internationally recognized experts and members of the interdisciplinary stroke team at the Massachusetts General Hospital and Harvard Medical School. The text is supported by numerous informative illustrations, and ease of reference is ensured through the inclusion of suitable tables. This book will serve as a unique source of up-to-date information for neurologists, emergency physicians, radiologists and other health care providers who care for the patient with acute ischemic stroke.
Download or read book Leveraging Clinical Imaging and Machine Learning Algorithms to Characterize Acute Ischemic Stroke Patients for Treatment Decision Making written by Jennifer Polson and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: For patients diagnosed with acute ischemic stroke, treatments such as thrombolysis and thrombectomy aim to restore blood flow to areas experiencing ischemia. These treatments have vastly improved outcomes, but it is currently unknown why some patients experience unsuccessful reperfusion or hemorrhagic complications. Taking advantage of recent advances in deep learning vision transformers, we developed algorithms for classification and prediction tasks regarding a patient's potential response to therapies using imaging taken at hospital admission. These models achieved higher generalization performance when identifying patients within the treatment window and those that will achieve successful recanalization. Our results illustrate that magnetic resonance (MR) and computed tomography (CT) imaging contains signal that can predict successful treatment response and that deep learning models can localize to salient regions within imaging without requiring time-intensive manual segmentation.
Download or read book Acute Stroke Nursing written by Jane Williams and published by John Wiley & Sons. This book was released on 2013-05-07 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stroke is a medical emergency that requires immediate medical attention. With active and efficient nursing management in the initial hours after stroke onset and throughout subsequent care, effective recovery and rehabilitation is increased. Acute Stroke Nursing provides an evidence-based, practical text facilitating the provision of optimal stroke care during the primary prevention, acute and continuing care phases. This timely and comprehensive text is structured to follow the acute stroke pathway experienced by patients. It explores the causes, symptoms and effects of stroke, and provides guidance on issues such as nutrition, continence, positioning, mobility and carer support. The text also considers rehabilitation, discharge planning, palliative care and the role of the nurse within the multi-professional team. Acute Stroke Nursing is the definitive reference on acute stroke for all nurses and healthcare professionals wishing to extend their knowledge of stroke nursing. Evidence-based and practical in style, with case studies and practice examples throughout Edited and authored by recognised stroke nursing experts, clinicians and leaders in the field of nursing practice, research and education The first text to explore stroke management from UK and international perspectives, and with a nursing focus
Download or read book Medical Image Analysis Methods written by Lena Costaridou and published by CRC Press. This book was released on 2005-07-13 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: To successfully detect and diagnose disease, it is vital for medical diagnosticians to properly apply the latest medical imaging technologies. It is a worrisome reality that due to either the nature or volume of some of the images provided, early or obscured signs of disease can go undetected or be misdiagnosed. To combat these inaccuracies, diagno
Download or read book Predicting Symptomatic Intracranial Haemorrhage in Acute Ischemic Stroke written by Florent Lépilliet and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ischemic stroke is a leading cause of death and disability in adult. Reperfusion therapies using intravenous thrombolysis (IVT) and endovascular interventions such as mechanical thrombectomy (MT) improve functional outcomes in patients with acute ischemic stroke (AIS) but unfortunately, these therapeutics increase the risk of intracranial haemorrhage (ICH) of ischemic brain tissue. Several definitions and classifications exist to define this complication, on a clinical or radiological level. However, high evidence indicates that symptomatic ICH (sICH) is the most relevant definition as it is most correlated with poor outcome. Several methods, based on clinical and/or radiological data, failed to predict the risk of haemorrhagic transformation in clinical practice. We attempted a new approach by training a supervised machine learning (ML) algorithm on clinical and MRI data within a 100 subjects cohort of patients with anterior circulation AIS treated by IVT and/or MT who underwent sICH (n=28), non-symptomatic ICH (n=27) and 45 controls with no bleeding, matched on clinical severity and age. We compared ML algorithm accuracy to the performance of the clinical Totaled Health Risks in Vascular Events (THRIVE) score and to the radiological Alberta Stroke Program Early CT Score applied to MR imaging (DWI-ASPECTS). ML algorithm predicted sICH with an Area Under receiver operating characteristic Curve (AUC) of 0.658 (CI 95% [0.534 - 0.783]). Applied in the cohort, estimated AUC of THRIVE score and DWI-ASPECTS were 0.664 (CI 95% [0.548 - 0.781]) and 0.634 (IC 95% [0.508 - 0.761]), respectively. Although it do not outperform current tools, this work showed that this algorithm was able to synthesize all clinical and radiological data provided and integrating the variety of information provided by MR imaging to provide a probability of sICH. Further studies are needed to improve these performances. Enlarging dataset is needed to improve learning phase, reduce overfitting risk and allow a 3D analysis to avoid data loss. More relevant clinical and radiological data could also be integrated to improve performances. Validation of these results on a more heterogeneous external population is also required.
Download or read book Artificial Intelligence in Medical Imaging written by Erik R. Ranschaert and published by Springer. This book was released on 2019-01-29 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.
Download or read book Artificial Intelligence and Cost effectiveness Analyses of Radiological Imaging in Acute Ischemic Stroke written by Henk van Voorst and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Acute ischemic stroke is caused by an occlusion of an artery in the brain. Current treatment options for acute ischemic stroke are intravenous thrombolysis and endovascular treatment. In this thesis, three parts describe varying analytical approaches to improve acute stroke care. Part I provides model-based health economic analyses of treatment decisions to improve acute stroke care. Specifically, the benefits of expedited endovascular treatment delivery and the use of CT perfusion for patient selection and occlusion detection are described. In Part II, prognostic imaging markers are studied. Deep learning-based quantification of white matter lesion volume in CT is compared to the radiologist-lead Fazekas scale for prognosticating functional outcome and intracranial hemorrhage occurrence. We studied if intravenous thrombolysis before endovascular treatment might be withheld based on increased risks for poor outcome and intracranial hemorrhage related to white matter lesion load. Furthermore, we evaluated thrombus volume, thrombus length, and thrombus radiomics as patient functional and endovascular treatment procedural outcome predictors. In Part III, we used generative adversarial networks to perform image-to-image translation. We translated CT scans with follow-up hemorrhagic or ischemic stroke lesions to baseline CT scans without. Furthermore, we remove contrast in CTA by translating a CTA to a non-contrast CT. Based on these translations we extract lesion segmentations in follow-up CT and vessel segmentations in CTA."--
Download or read book Deep Learning for Medical Image Analysis written by S. Kevin Zhou and published by Academic Press. This book was released on 2023-12-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, segmentation, registration, and computer-aided analysis. · Covers common research problems in medical image analysis and their challenges · Describes the latest deep learning methods and the theories behind approaches for medical image analysis · Teaches how algorithms are applied to a broad range of application areas including cardiac, neural and functional, colonoscopy, OCTA applications and model assessment · Includes a Foreword written by Nicholas Ayache
Download or read book Magnetic Particle Imaging written by Tobias Knopp and published by Springer Science & Business Media. This book was released on 2012-05-04 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides a comprehensive overview of recent developments in magnetic particle imaging (MPI), a novel imaging modality. Using various static and oscillating magnetic fields, and tracer materials made from iron oxide nanoparticles, MPI can perform background-free measurements of the particles’ local concentration. The method exploits the nonlinear remagnetization behavior of the particles and has the potential to surpass current methods for the detection of iron oxide in terms of sensitivity and spatiotemporal resolution. Starting from an introduction to the technology, the topics addressed include setting up an imaging device, assessment of image quality, development of new MPI tracer materials, and the first preclinical results. This is the first book to be published on magnetic particle imaging, and it will be an invaluable source of information for everyone with an interest in this exciting new modality.
Download or read book Machine Learning in Medical Imaging written by Mingxia Liu and published by Springer Nature. This book was released on 2020-10-02 with total page 702 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 11th International Workshop on Machine Learning in Medical Imaging, MLMI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 68 papers presented in this volume were carefully reviewed and selected from 101 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.
Download or read book Textbook of Stroke Medicine written by Michael Brainin and published by Cambridge University Press. This book was released on 2014-09-11 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fully revised throughout, the new edition of this concise textbook is aimed at doctors preparing to specialize in stroke care.
