Artificial Intelligence For Medical Image Analysis Of Neuroimaging Data

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Artificial Intelligence In Medical Imaging
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Author : Erik R. Ranschaert
language : en
Publisher: Springer
Release Date : 2019-01-29
Artificial Intelligence In Medical Imaging written by Erik R. Ranschaert and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-29 with Medical categories.
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 implicationsfor 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.
Artificial Intelligence For Medical Image Analysis Of Neuroimaging Data
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Author : Nianyin Zeng
language : en
Publisher: Frontiers Media SA
Release Date : 2020-07-03
Artificial Intelligence For Medical Image Analysis Of Neuroimaging Data written by Nianyin Zeng and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-03 with categories.
Deep Learning For Medical Image Analysis
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Author : S. Kevin Zhou
language : en
Publisher: Academic Press
Release Date : 2017-01-18
Deep Learning For Medical Image Analysis written by S. Kevin Zhou and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-18 with Computers categories.
Deep learning is providing exciting solutions for medical image analysis problems and is seen as 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 have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Covers common research problems in medical image analysis and their challenges Describes 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 Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. Includes a Foreword written by Nicholas Ayache
Medical Image Computing And Computer Assisted Intervention Miccai 2020
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Author : Anne L. Martel
language : en
Publisher: Springer Nature
Release Date : 2020-10-02
Medical Image Computing And Computer Assisted Intervention Miccai 2020 written by Anne L. Martel and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-02 with Computers categories.
The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis Part IV: segmentation; shape models and landmark detection Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging Part VI: brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography
Clinical Image Based Procedures Fairness Of Ai In Medical Imaging And Ethical And Philosophical Issues In Medical Imaging
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Author : Stefan Wesarg
language : en
Publisher: Springer Nature
Release Date : 2023-10-09
Clinical Image Based Procedures Fairness Of Ai In Medical Imaging And Ethical And Philosophical Issues In Medical Imaging written by Stefan Wesarg and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-09 with Computers categories.
This book constitutes the refereed proceedings of the 12th International Workshop on Clinical Image-Based Procedures, CLIP 2023, the First MICCAI Workshop on Fairness of AI in Medical Imaging, FAIMI 2023, and the Second MICCAI Workshop on the Ethical and Philosophical Issues in Medical Imaging, EPIMI 2023, held in conjunction with MICCAI 2023, in October 2023. CLIP 2023 accepted 5 full papers and 3 short papers form 8 submissions received. It focuses on holistic patient models for personalized healthcare with the goal to bring basic research methods closer to the clinical practice. For FAIMI 2023, 19 full papers have been accepted from 20 submissions. They focus on creating awareness about potential fairness issues that can emerge in the context of machine learning. And for EPIMI 2023, 2 papers have been accepted from 5 submissions. They investigate questions that underlie medical imaging research at the most fundamental level.
Biomedical Imaging
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Author : Ankur Gogoi
language : en
Publisher: Springer Nature
Release Date : 2024-09-26
Biomedical Imaging written by Ankur Gogoi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-26 with Science categories.
This book presents the rapidly developing field of artificial intelligence and machine learning and its application in biomedical imaging. As is known, starting from the diagnosis of fractures by using X-rays to understanding the complex structure and function of the brain, biomedical imaging has contributed immensely toward the development of precision diagnosis and treatment strategies for numerous diseases. While continuous evolution in imaging technologies have enabled the acquisition of images having resolution and contrast far better than ever, it significantly increased the volume of data associated with each image scan—making it increasingly difficult for experts to analyze and interpret. In this context, the application of artificial intelligence (AI) and machine learning (ML) tools has become one of the most exciting frontlines of contemporary research in biomedical imaging due to their capability to extract minute traces of various disease signatures from large and complicated datasets and providing clear insight into the potential abnormalities with excellent accuracy, sensitivity, and specificity. The hallmark of this book will be the contributions from international leaders on different AI-aided advanced biomedical imaging modalities and techniques. Included will be comprehensive description of several of the technology-driven spectacular advances made over the past few years that have allowed early detection and delineation of abnormalities with sub-pixel image segmentation and classification. Starting from the fundamentals of biomedical image processing, the book presents a streamlined and focused coverage of the core principles, theoretical and experimental approaches, and state-of-the-art applications of most of the currently used biomedical imaging techniques powered by AI.
Explainable Ai In Healthcare Imaging For Medical Diagnoses
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Author : Tanzila Saba
language : en
Publisher: Elsevier
Release Date : 2025-03-29
Explainable Ai In Healthcare Imaging For Medical Diagnoses written by Tanzila Saba and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-29 with Computers categories.
In an era where Artificial Intelligence (AI) is revolutionizing healthcare, Explainable AI in Healthcare Imaging for Precision Medicine addresses the critical need for transparency, trust, and accountability in AI-driven medical technologies. As AI becomes an integral part of clinical decision-making, especially in imaging and precision medicine, the question of how AI reaches its conclusions grows increasingly significant. This book explores how Explainable AI (XAI) is transforming healthcare by making AI systems more interpretable, reliable, and transparent, empowering clinicians and enhancing patient outcomes.Through a comprehensive examination of the latest research, real-world case studies, and expert insights, this book delves into the application of XAI in medical imaging, disease diagnosis, treatment planning, and personalized care. It discusses the technical methodologies behind XAI, the challenges and opportunities of its integration into healthcare, and the ethical and regulatory considerations that will shape the future of AI-assisted medical decisions.Key areas of focus include the role of XAI in improving diagnostic accuracy in fields such as radiology, pathology, and genomics and its potential to enhance collaboration between AI systems, healthcare professionals, and patients. The book also highlights practical applications of XAI in personalized medicine, showing how explainable models help tailor treatments to individual patients, and discusses how XAI can contribute to reducing bias and improving fairness in medical decision-making.Written by leading experts in AI, healthcare, and precision medicine, Explain[S3G1] able AI in Healthcare Imaging for Precision Medicine is an essential resource for researchers, clinicians, students, and policymakers. Whether you are looking to stay at the forefront of AI innovations in healthcare or seeking to understand how explainability can build trust in AI systems, this book provides the insights and knowledge needed to navigate the evolving landscape of AI in medicine. It invites readers to explore how XAI can revolutionize healthcare and precision medicine, shaping a future where AI is both powerful and trustworthy. - Provides step-by-step procedures to build a digital human model - Assists in validating predicted human motion using simulations and experiments - Offers formulation optimization features for dynamic human motion prediction
Artificial Intelligence And Its Practical Applications In The Digital Economy
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Author : Yahya Mohamed Elhadj
language : en
Publisher: Springer Nature
Release Date : 2024-12-17
Artificial Intelligence And Its Practical Applications In The Digital Economy written by Yahya Mohamed Elhadj and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-17 with Computers categories.
Artificial Intelligence (AI) technologies hold immense promise for developing countries by offering innovative solutions to longstanding challenges. By leveraging AI in health care, education, economic development, infrastructure, and resource management, these countries can potentially leapfrog traditional development stages and improve the quality of life for their populations. However, it's essential to approach AI deployment with ethical considerations to ensure that the technology serves the best interests of these communities and thus to maximize the expected benefits. The I2COMSAPP'24 "International Conference on Artificial Intelligence and its Applications in the Age of Digital Transformation" aims to provide an excellent opportunity to gather experts, researchers, practitioners, and innovators from various fields to explore the latest advancements, challenges, and practical implementations of artificial intelligence and machine learning (ML) technologies. Moreover, it aims to foster knowledge sharing, collaboration, and networking among professionals who are driving responsible and innovative use of AI and leveraging real-world applications for the betterment of society and industries.
Artificial Intelligence Based Computer Aided Diagnosis Applications For Brain Disorders From Medical Imaging Data Volume Ii
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Author : Ahmed Shalaby
language : en
Publisher: Frontiers Media SA
Release Date : 2023-08-02
Artificial Intelligence Based Computer Aided Diagnosis Applications For Brain Disorders From Medical Imaging Data Volume Ii written by Ahmed Shalaby and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-02 with Science categories.
Machine Learning And Deep Learning Techniques For Medical Science
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Author : K. Gayathri Devi
language : en
Publisher: CRC Press
Release Date : 2022-05-11
Machine Learning And Deep Learning Techniques For Medical Science written by K. Gayathri Devi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-11 with Technology & Engineering categories.
The application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time required by doctors, radiologists, and other medical professionals for analyzing, predicting, and diagnosing the conditions with accurate results. The book offers important key aspects in the development and implementation of ML and DL approaches toward developing prediction tools and models and improving medical diagnosis. The contributors explore the recent trends, innovations, challenges, and solutions, as well as case studies of the applications of ML and DL in intelligent system-based disease diagnosis. The chapters also highlight the basics and the need for applying mathematical aspects with reference to the development of new medical models. Authors also explore ML and DL in relation to artificial intelligence (AI) prediction tools, the discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, and pattern recognition approaches to functional magnetic resonance imaging images. This book is for students and researchers of computer science and engineering, electronics and communication engineering, and information technology; for biomedical engineering researchers, academicians, and educators; and for students and professionals in other areas of the healthcare sector. Presents key aspects in the development and the implementation of ML and DL approaches toward developing prediction tools, models, and improving medical diagnosis Discusses the recent trends, innovations, challenges, solutions, and applications of intelligent system-based disease diagnosis Examines DL theories, models, and tools to enhance health information systems Explores ML and DL in relation to AI prediction tools, discovery of drugs, neuroscience, and diagnosis in multiple imaging modalities Dr. K. Gayathri Devi is a Professor at the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamil Nadu, India. Dr. Kishore Balasubramanian is an Assistant Professor (Senior Scale) at the Department of EEE at Dr. Mahalingam College of Engineering & Technology, Tamil Nadu, India. Dr. Le Anh Ngoc is a Director of Swinburne Innovation Space and Professor in Swinburne University of Technology (Vietnam).