Medical Applications of Laser Molecular Imaging and Machine Learning

Medical Applications of Laser Molecular Imaging and Machine Learning PDF Author: Yury V. Kistenev
Publisher:
ISBN: 9781510645349
Category :
Languages : en
Pages : 252

Get Book

Book Description

Medical Applications of Laser Molecular Imaging and Machine Learning

Medical Applications of Laser Molecular Imaging and Machine Learning PDF Author: Yury V. Kistenev
Publisher:
ISBN: 9781510645349
Category :
Languages : en
Pages : 252

Get Book

Book Description


Advances in Brain Imaging Techniques

Advances in Brain Imaging Techniques PDF Author: Nirmal Mazumder
Publisher: Springer Nature
ISBN: 9811913528
Category : Medical
Languages : en
Pages : 265

Get Book

Book Description
The book reviews the recent developments in brain imaging and their technological advancements to understand molecular mechanisms associated with neurological disorders and basic behaviors in humans and rodents at the structural, molecular, and functional levels. It discusses the usefulness of advanced optical microscopy techniques, including optical coherence tomography (OCT), miniscope, multiphoton fluorescence (2PF & 3PF), adaptive optics, harmonic generation, and Raman microscopy for understanding pathomechanism of brain disorders and pathological and physiological changes associated with neurodegenerative diseases. Also, the book presents conventional imaging modalities, including Magnetic Resonance Imaging (MRI), for delineating underlying mechanisms and precise early diagnosis of neurological disorders. This book is a useful resource for neuroscientists and researchers working in biomedical engineering and optics.

Artificial Intelligence/Machine Learning in Nuclear Medicine and Hybrid Imaging

Artificial Intelligence/Machine Learning in Nuclear Medicine and Hybrid Imaging PDF Author: Patrick Veit-Haibach
Publisher: Springer Nature
ISBN: 3031001192
Category : Medical
Languages : en
Pages : 217

Get Book

Book Description
This book includes detailed explanations of the underlying technologies and concepts used in Artificial Intelligence (AI) and Machine Learning (ML) in the context of nuclear medicine and hybrid imaging. A diverse team of authors, including pioneers in the field and respected experts from leading international institutions, share their insights, opinions and outlooks on this exciting topic. A wide range of clinical applications are discussed, from brain applications to body indications, as well as the applicability of AI and ML for cardio-vascular conditions. The book also considers the potential impact of theranostics. To balance the technology-heavy and disease-specific applications, it also discusses ethical / legal issues, economic realities and the human factor, the physician. Though this discussion is not based on research and outcomes, it provides important insights into the ramifications of how AI and ML could transform Nuclear Medicine and Hybrid Imaging practice. As the first work highlighting the role of these concepts specifically in this field, rather than for medical imaging in general, this book offers a valuable resource for Nuclear Medicine Physicians, Radiologists, Physicists, Medical Imaging Administrators and Nuclear Medicine Technologists alike.

Deep Learning Applications in Medical Imaging

Deep Learning Applications in Medical Imaging PDF Author: Saxena, Sanjay
Publisher: IGI Global
ISBN: 1799850722
Category : Medical
Languages : en
Pages : 274

Get Book

Book Description
Before the modern age of medicine, the chance of surviving a terminal disease such as cancer was minimal at best. After embracing the age of computer-aided medical analysis technologies, however, detecting and preventing individuals from contracting a variety of life-threatening diseases has led to a greater survival percentage and increased the development of algorithmic technologies in healthcare. Deep Learning Applications in Medical Imaging is a pivotal reference source that provides vital research on the application of generating pictorial depictions of the interior of a body for medical intervention and clinical analysis. While highlighting topics such as artificial neural networks, disease prediction, and healthcare analysis, this publication explores image acquisition and pattern recognition as well as the methods of treatment and care. This book is ideally designed for diagnosticians, medical imaging specialists, healthcare professionals, physicians, medical researchers, academicians, and students.

Machine Learning in Medical Imaging

Machine Learning in Medical Imaging PDF Author: Xiaohuan Cao
Publisher: Springer Nature
ISBN: 3031456769
Category : Computers
Languages : en
Pages : 501

Get Book

Book Description
The two-volume set LNCS 14348 and 14139 constitutes the proceedings of the 14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023, held in conjunction with MICCAI 2023, in Vancouver, Canada, in October 2023. The 93 full papers presented in the proceedings were carefully reviewed and selected from 139 submissions. They focus on major trends and challenges in artificial intelligence and machine learning in the medical imaging field, translating medical imaging research into clinical practice. Topics of interests included deep learning, generative adversarial learning, ensemble learning, transfer learning, multi-task learning, manifold learning, reinforcement learning, along with their applications to medical image analysis, computer-aided diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.

Machine Learning in Medical Imaging

Machine Learning in Medical Imaging PDF Author: Xiaohuan Cao
Publisher: Springer Nature
ISBN: 3031456734
Category : Computers
Languages : en
Pages : 499

Get Book

Book Description
The two-volume set LNCS 14348 and 14139 constitutes the proceedings of the 14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023, held in conjunction with MICCAI 2023, in Vancouver, Canada, in October 2023. The 93 full papers presented in the proceedings were carefully reviewed and selected from 139 submissions. They focus on major trends and challenges in artificial intelligence and machine learning in the medical imaging field, translating medical imaging research into clinical practice. Topics of interests included deep learning, generative adversarial learning, ensemble learning, transfer learning, multi-task learning, manifold learning, reinforcement learning, along with their applications to medical image analysis, computer-aided diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.

Applications of Artificial Intelligence in Medical Imaging

Applications of Artificial Intelligence in Medical Imaging PDF Author: Abdulhamit Subasi
Publisher: Academic Press
ISBN: 0443184518
Category : Science
Languages : en
Pages : 381

Get Book

Book Description
Applications of Artificial Intelligence in Medical Imaging provides the description of various biomedical image analysis in disease detection using AI that can be used to incorporate knowledge obtained from different medical imaging devices such as CT, X-ray, PET and ultrasound. The book discusses the use of AI for detection of several cancer types, including brain tumor, breast, pancreatic, rectal, lung colon, and skin. In addition, it explains how AI and deep learning techniques can be used to diagnose Alzheimer's, Parkinson's, COVID-19 and mental conditions. This is a valuable resource for clinicians, researchers and healthcare professionals who are interested in learning more about AI and its impact in medical/biomedical image analysis. Discusses new deep learning algorithms for image analysis and how they are used for medical images Provides several examples for each imaging technique, along with their application areas so that readers can rely on them as a clinical decision support system Describes how new AI tools may contribute significantly to the successful enhancement of a single patient's clinical knowledge to improve treatment outcomes

Future Trends and Challenges of Molecular Imaging and AI Innovation

Future Trends and Challenges of Molecular Imaging and AI Innovation PDF Author: Kang-Ping Lin
Publisher: Springer Nature
ISBN: 3030927865
Category : Science
Languages : en
Pages : 96

Get Book

Book Description
This volumes presents the proceedings of the FASMI 2020 conference, held at Taipei Veterans General Hospital on November 20-22, 2020. It presents contributions on all aspects of molecular imaging, discovered by leading academic scientists and researchers. It also provides a premier interdisciplinary treatment of recent innovations, trend, and concerns as well as practical challenges and solutions in Molecular Imaging and put an emphasis on Artificial Intelligence applied to Imaging Data. FASMI is the annual meeting of the Federation of Asian Societies for Molecular Imaging

Machine Learning in Medical Imaging

Machine Learning in Medical Imaging PDF Author: Chunfeng Lian
Publisher: Springer Nature
ISBN: 303087589X
Category : Computers
Languages : en
Pages : 723

Get Book

Book Description
This book constitutes the proceedings of the 12th International Workshop on Machine Learning in Medical Imaging, MLMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.* The 71 papers presented in this volume were carefully reviewed and selected from 92 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. *The workshop was held virtually.

Machine Learning in Medical Imaging

Machine Learning in Medical Imaging PDF Author: Chunfeng Lian
Publisher: Springer Nature
ISBN: 303121014X
Category : Computers
Languages : en
Pages : 491

Get Book

Book Description
This book constitutes the proceedings of the 13th International Workshop on Machine Learning in Medical Imaging, MLMI 2022, held in conjunction with MICCAI 2022, in Singapore, in September 2022. The 48 full papers presented in this volume were carefully reviewed and selected from 64 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.