Medical Imaging

Medical Imaging
Author: K.C. Santosh,Sameer Antani,DS Guru,Nilanjan Dey
Publsiher: CRC Press
Total Pages: 238
Release: 2019-08-20
ISBN: 0429642490
Category: Computers
Language: EN, FR, DE, ES & NL

Medical Imaging Book Excerpt:

The book discusses varied topics pertaining to advanced or up-to-date techniques in medical imaging using artificial intelligence (AI), image recognition (IR) and machine learning (ML) algorithms/techniques. Further, coverage includes analysis of chest radiographs (chest x-rays) via stacked generalization models, TB type detection using slice separation approach, brain tumor image segmentation via deep learning, mammogram mass separation, epileptic seizures, breast ultrasound images, knee joint x-ray images, bone fracture detection and labeling, and diabetic retinopathy. It also reviews 3D imaging in biomedical applications and pathological medical imaging.

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
Author: Lia Morra,Silvia Delsanto,Loredana Correale
Publsiher: CRC Press
Total Pages: 152
Release: 2019-11-25
ISBN: 1000753085
Category: Science
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medical Imaging Book Excerpt:

This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
Author: Erik R. Ranschaert,Sergey Morozov,Paul R. Algra
Publsiher: Springer
Total Pages: 373
Release: 2019-01-29
ISBN: 3319948784
Category: Medical
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medical Imaging 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.

Artificial Intelligence Machine Learning in Nuclear Medicine and Hybrid Imaging

Artificial Intelligence Machine Learning in Nuclear Medicine and Hybrid Imaging
Author: Patrick Veit-Haibach,Ken Herrmann
Publsiher: Springer Nature
Total Pages: 210
Release: 2022-06-22
ISBN: 3031001192
Category: Medical
Language: EN, FR, DE, ES & NL

Artificial Intelligence Machine Learning in Nuclear Medicine and Hybrid Imaging Book Excerpt:

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.

Artificial Intelligence in Healthcare and Medicine

Artificial Intelligence in Healthcare and Medicine
Author: Kayvan Najarian,Delaram Kahrobaei,Enrique Dominguez,Reza Soroushmehr
Publsiher: CRC Press
Total Pages: 300
Release: 2022-04-06
ISBN: 1000565815
Category: Computers
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Healthcare and Medicine Book Excerpt:

This book provides a comprehensive overview of the recent developments in clinical decision support systems, precision health, and data science in medicine. The book targets clinical researchers and computational scientists seeking to understand the recent advances of artificial intelligence (AI) in health and medicine. Since AI and its applications are believed to have the potential to revolutionize healthcare and medicine, there is a clear need to explore and investigate the state-of-the-art advancements in the field. This book provides a detailed description of the advancements, challenges, and opportunities of using AI in medical and health applications. Over 10 case studies are included in the book that cover topics related to biomedical image processing, machine learning for healthcare, clinical decision support systems, visualization of high dimensional data, data security and privacy, bioinformatics, and biometrics. The book is intended for clinical researchers and computational scientists seeking to understand the recent advances of AI in health and medicine. Many universities may use the book as a secondary training text. Companies in the healthcare sector can greatly benefit from the case studies covered in the book. Moreover, this book also: Provides an overview of the recent developments in clinical decision support systems, precision health, and data science in medicine Examines the advancements, challenges, and opportunities of using AI in medical and health applications Includes 10 cases for practical application and reference Kayvan Najarian is a Professor in the Department of Computational Medicine and Bioinformatics, Department of Electrical Engineering and Computer Science, and Department of Emergency Medicine at the University of Michigan, Ann Arbor. Delaram Kahrobaei is the University Dean for Research at City University of New York (CUNY), a Professor of Computer Science and Mathematics, Queens College CUNY, and the former Chair of Cyber Security, University of York. Enrique Domínguez is a professor in the Department of Computer Science at the University of Malaga and a member of the Biomedical Research Institute of Malaga. Reza Soroushmehr is a Research Assistant Professor in the Department of Computational Medicine and Bioinformatics and a member of the Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor.

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
Author: Lia Morra,Silvia Delsanto,Loredana Correale
Publsiher: CRC Press
Total Pages: 152
Release: 2019-11-25
ISBN: 1000753204
Category: Science
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medical Imaging Book Excerpt:

This book, written by authors with more than a decade of experience in the design and development of artificial intelligence (AI) systems in medical imaging, will guide readers in the understanding of one of the most exciting fields today. After an introductory description of classical machine learning techniques, the fundamentals of deep learning are explained in a simple yet comprehensive manner. The book then proceeds with a historical perspective of how medical AI developed in time, detailing which applications triumphed and which failed, from the era of computer aided detection systems on to the current cutting-edge applications in deep learning today, which are starting to exhibit on-par performance with clinical experts. In the last section, the book offers a view on the complexity of the validation of artificial intelligence applications for commercial use, describing the recently introduced concept of software as a medical device, as well as good practices and relevant considerations for training and testing machine learning systems for medical use. Open problematics on the validation for public use of systems which by nature continuously evolve through new data is also explored. The book will be of interest to graduate students in medical physics, biomedical engineering and computer science, in addition to researchers and medical professionals operating in the medical imaging domain, who wish to better understand these technologies and the future of the field. Features: An accessible yet detailed overview of the field Explores a hot and growing topic Provides an interdisciplinary perspective

Artificial Intelligence and Machine Learning in 2D 3D Medical Image Processing

Artificial Intelligence and Machine Learning in 2D 3D Medical Image Processing
Author: Rohit Raja,Sandeep Kumar,Shilpa Rani,K. Ramya Laxmi
Publsiher: CRC Press
Total Pages: 196
Release: 2020-12-22
ISBN: 1000337073
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Machine Learning in 2D 3D Medical Image Processing Book Excerpt:

Digital images have several benefits, such as faster and inexpensive processing cost, easy storage and communication, immediate quality assessment, multiple copying while preserving quality, swift and economical reproduction, and adaptable manipulation. Digital medical images play a vital role in everyday life. Medical imaging is the process of producing visible images of inner structures of the body for scientific and medical study and treatment as well as a view of the function of interior tissues. This process pursues disorder identification and management. Medical imaging in 2D and 3D includes many techniques and operations such as image gaining, storage, presentation, and communication. The 2D and 3D images can be processed in multiple dimensions. Depending on the requirement of a specific problem, one must identify various features of 2D or 3D images while applying suitable algorithms. These image processing techniques began in the 1960s and were used in such fields as space, clinical purposes, the arts, and television image improvement. In the 1970s, with the development of computer systems, the cost of image processing was reduced and processes became faster. In the 2000s, image processing became quicker, inexpensive, and simpler. In the 2020s, image processing has become a more accurate, more efficient, and self-learning technology. This book highlights the framework of the robust and novel methods for medical image processing techniques in 2D and 3D. The chapters explore existing and emerging image challenges and opportunities in the medical field using various medical image processing techniques. The book discusses real-time applications for artificial intelligence and machine learning in medical image processing. The authors also discuss implementation strategies and future research directions for the design and application requirements of these systems. This book will benefit researchers in the medical image processing field as well as those looking to promote the mutual understanding of researchers within different disciplines that incorporate AI and machine learning. FEATURES Highlights the framework of robust and novel methods for medical image processing techniques Discusses implementation strategies and future research directions for the design and application requirements of medical imaging Examines real-time application needs Explores existing and emerging image challenges and opportunities in the medical field

Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging

Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging
Author: Kenji Suzuki,Yisong Chen
Publsiher: Springer
Total Pages: 387
Release: 2018-01-09
ISBN: 331968843X
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging Book Excerpt:

This book offers the first comprehensive overview of artificial intelligence (AI) technologies in decision support systems for diagnosis based on medical images, presenting cutting-edge insights from thirteen leading research groups around the world. Medical imaging offers essential information on patients’ medical condition, and clues to causes of their symptoms and diseases. Modern imaging modalities, however, also produce a large number of images that physicians have to accurately interpret. This can lead to an “information overload” for physicians, and can complicate their decision-making. As such, intelligent decision support systems have become a vital element in medical-image-based diagnosis and treatment. Presenting extensive information on this growing field of AI, the book offers a valuable reference guide for professors, students, researchers and professionals who want to learn about the most recent developments and advances in the field.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Author: Lei Xing,Maryellen L. Giger,James K. Min
Publsiher: Academic Press
Total Pages: 568
Release: 2020-09-03
ISBN: 0128212586
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medicine Book Excerpt:

Artificial Intelligence Medicine: Technical Basis and Clinical Applications presents a comprehensive overview of the field, ranging from its history and technical foundations, to specific clinical applications and finally to prospects. Artificial Intelligence (AI) is expanding across all domains at a breakneck speed. Medicine, with the availability of large multidimensional datasets, lends itself to strong potential advancement with the appropriate harnessing of AI. The integration of AI can occur throughout the continuum of medicine: from basic laboratory discovery to clinical application and healthcare delivery. Integrating AI within medicine has been met with both excitement and scepticism. By understanding how AI works, and developing an appreciation for both limitations and strengths, clinicians can harness its computational power to streamline workflow and improve patient care. It also provides the opportunity to improve upon research methodologies beyond what is currently available using traditional statistical approaches. On the other hand, computers scientists and data analysts can provide solutions, but often lack easy access to clinical insight that may help focus their efforts. This book provides vital background knowledge to help bring these two groups together, and to engage in more streamlined dialogue to yield productive collaborative solutions in the field of medicine. Provides history and overview of artificial intelligence, as narrated by pioneers in the field Discusses broad and deep background and updates on recent advances in both medicine and artificial intelligence that enabled the application of artificial intelligence Addresses the ever-expanding application of this novel technology and discusses some of the unique challenges associated with such an approach

AI Innovation in Medical Imaging Diagnostics

AI Innovation in Medical Imaging Diagnostics
Author: Anbarasan, Kalaivani
Publsiher: IGI Global
Total Pages: 248
Release: 2021-01-01
ISBN: 1799830934
Category: Medical
Language: EN, FR, DE, ES & NL

AI Innovation in Medical Imaging Diagnostics Book Excerpt:

Recent advancements in the technology of medical imaging, such as CT and MRI scanners, are making it possible to create more detailed 3D and 4D images. These powerful images require vast amounts of digital data to help with the diagnosis of the patient. Artificial intelligence (AI) must play a vital role in supporting with the analysis of this medical imaging data, but it will only be viable as long as healthcare professionals and AI interact to embrace deep thinking platforms such as automation in the identification of diseases in patients. AI Innovation in Medical Imaging Diagnostics is an essential reference source that examines AI applications in medical imaging that can transform hospitals to become more efficient in the management of patient treatment plans through the production of faster imaging and the reduction of radiation dosages through the PET and SPECT imaging modalities. The book also explores how data clusters from these images can be translated into small data packages that can be accessed by healthcare departments to give a real-time insight into patient care and required interventions. Featuring research on topics such as assistive healthcare, cancer detection, and machine learning, this book is ideally designed for healthcare administrators, radiologists, data analysts, computer science professionals, medical imaging specialists, diagnosticians, medical professionals, researchers, and students.

Artificial Intelligence and PET Imaging Part 1 An Issue of PET Clinics

Artificial Intelligence and PET Imaging  Part 1  An Issue of PET Clinics
Author: Babak Saboury,Eliot Siegel
Publsiher: Elsevier Health Sciences
Total Pages: 240
Release: 2021-09-21
ISBN: 0323835619
Category: Medical
Language: EN, FR, DE, ES & NL

Artificial Intelligence and PET Imaging Part 1 An Issue of PET Clinics Book Excerpt:

Artificial Intelligence and PET Imaging, Part 1, An Issue of PET Clinics, E-Book

Artificial Intelligence in Radiology An Issue of Radiologic Clinics of North America E Book

Artificial Intelligence in Radiology  An Issue of Radiologic Clinics of North America  E Book
Author: Daniel L. Rubin
Publsiher: Elsevier Health Sciences
Total Pages: 240
Release: 2021-10-27
ISBN: 0323813569
Category: Medical
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Radiology An Issue of Radiologic Clinics of North America E Book Book Excerpt:

Artificial Intelligence in Radiology, An Issue of Radiologic Clinics of North America, E-Book

Medical Applications of Artificial Intelligence

Medical Applications of Artificial Intelligence
Author: Arvin Agah
Publsiher: CRC Press
Total Pages: 526
Release: 2013-11-06
ISBN: 1439884331
Category: Medical
Language: EN, FR, DE, ES & NL

Medical Applications of Artificial Intelligence Book Excerpt:

Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Applications of Artificial Intelligence reviews the research, focusing on state-of-the-art projects in the field. The book captures the breadth and depth of the medical applications of artificial intelligence, exploring new developments and persistent challenges.

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
Author: David Gerald
Publsiher: Unknown
Total Pages: 188
Release: 2021-06-10
ISBN: 1928374650XXX
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Artificial Intelligence in Medical Imaging Book Excerpt:

Contents COVID-19 pathways for brain and heart injury in comorbidity patients: A role of medical imaging and artificial intelligence-based COVID severity classification Triboelectric nanogenerator based self-powered sensor for artificial intelligence Artificial intelligence (AI) impacting diagnosis of glaucoma and understanding the regulatory aspects of AI-based software as medical device Variants of Artificial Bee Colony algorithm and its applications in medical image processing Keyword artificial intelligence in medical imaging Artificial Intelligence In Healthcare Artificial Intelligence in Medicine the Health IT artificial intelligence in precision health Healthcare applications Biomedical research Epileptic seizure Artificial intelligence Deep Learning Multi-source time-series Healthcare Emergency Medicine Celiac disease image analysis Nanotechnology Artificial intelligence Dentistry Fuzzy logic Artificial neural network Genetic algorithms Augmented and virtual reality the nuclear medicine field nuclear medicine AI in oncology indi- vidualized medicine assaying patients' genetic makeup (genome), Genomics genomics and personalized medicine what everyone needs to know maceutical clinical research and healthcare

Computational Intelligence in Medical Imaging

Computational Intelligence in Medical Imaging
Author: G. Schaefer,A. Hassanien,J. Jiang
Publsiher: Chapman & Hall/CRC
Total Pages: 510
Release: 2017-09-12
ISBN: 9781138112209
Category: Electronic Book
Language: EN, FR, DE, ES & NL

Computational Intelligence in Medical Imaging Book Excerpt:

CI Techniques & Algorithms for a Variety of Medical Imaging Situations Documents recent advances and stimulates further research A compilation of the latest trends in the field, Computational Intelligence in Medical Imaging: Techniques and Applications explores how intelligent computing can bring enormous benefit to existing technology in medical image processing as well as improve medical imaging research. The contributors also cover state-of-the-art research toward integrating medical image processing with artificial intelligence and machine learning approaches. The book presents numerous techniques, algorithms, and models. It describes neural networks, evolutionary optimization techniques, rough sets, support vector machines, tabu search, fuzzy logic, a Bayesian probabilistic framework, a statistical parts-based appearance model, a reinforcement learning-based multistage image segmentation algorithm, a machine learning approach, Monte Carlo simulations, and intelligent, deformable models. The contributors discuss how these techniques are used to classify wound images, extract the boundaries of skin lesions, analyze prostate cancer, handle the inherent uncertainties in mammographic images, and encapsulate the natural intersubject anatomical variance in medical images. They also examine prostate segmentation in transrectal ultrasound images, automatic segmentation and diagnosis of bone scintigraphy, 3-D medical image segmentation, and the reconstruction of SPECT and PET tomographic images.

Artificial Intelligence and PET Imaging Part 2 An Issue of PET Clinics E Book

Artificial Intelligence and PET Imaging  Part 2  An Issue of PET Clinics   E Book
Author: Arman Rahmim,Babak Saboury,Eliot Siegel
Publsiher: Elsevier Health Sciences
Total Pages: 240
Release: 2021-11-27
ISBN: 0323850146
Category: Medical
Language: EN, FR, DE, ES & NL

Artificial Intelligence and PET Imaging Part 2 An Issue of PET Clinics E Book Book Excerpt:

In this issue of PET Clinics, guest editors Arman Rahmim, Babak Saboury, and Eliot Siegel bring their considerable expertise to the topic of Artificial Intelligence and PET Imaging. Provides in-depth, clinical reviews on the latest updates in AI and PET Imaging, providing actionable insights for clinical practice. Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field; Authors synthesize and distill the latest research and practice guidelines to create these timely topic-based reviews.

Healthcare and Artificial Intelligence

Healthcare and Artificial Intelligence
Author: Bernard Nordlinger,Cédric Villani,Daniela Rus
Publsiher: Springer Nature
Total Pages: 279
Release: 2020-03-17
ISBN: 3030321614
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Healthcare and Artificial Intelligence Book Excerpt:

This book provides an overview of the role of AI in medicine and, more generally, of issues at the intersection of mathematics, informatics, and medicine. It is intended for AI experts, offering them a valuable retrospective and a global vision for the future, as well as for non-experts who are curious about this timely and important subject. Its goal is to provide clear, objective, and reasonable information on the issues covered, avoiding any fantasies that the topic “AI” might evoke. In addition, the book seeks to provide a broad kaleidoscopic perspective, rather than deep technical details.

Medical Imaging and Health Informatics

Medical Imaging and Health Informatics
Author: Tushar H. Jaware,K. Sarat Kumar,Ravindra D. Badgujar,Svetlin Antonov
Publsiher: John Wiley & Sons
Total Pages: 384
Release: 2022-05-26
ISBN: 1119819148
Category: Computers
Language: EN, FR, DE, ES & NL

Medical Imaging and Health Informatics Book Excerpt:

MEDICAL IMAGING AND HEALTH INFORMATICS Provides a comprehensive review of artificial intelligence (AI) in medical imaging as well as practical recommendations for the usage of machine learning (ML) and deep learning (DL) techniques for clinical applications. Medical imaging and health informatics is a subfield of science and engineering which applies informatics to medicine and includes the study of design, development, and application of computational innovations to improve healthcare. The health domain has a wide range of challenges that can be addressed using computational approaches; therefore, the use of AI and associated technologies is becoming more common in society and healthcare. Currently, deep learning algorithms are a promising option for automated disease detection with high accuracy. Clinical data analysis employing these deep learning algorithms allows physicians to detect diseases earlier and treat patients more efficiently. Since these technologies have the potential to transform many aspects of patient care, disease detection, disease progression and pharmaceutical organization, approaches such as deep learning algorithms, convolutional neural networks, and image processing techniques are explored in this book. This book also delves into a wide range of image segmentation, classification, registration, computer-aided analysis applications, methodologies, algorithms, platforms, and tools; and gives a holistic approach to the application of AI in healthcare through case studies and innovative applications. It also shows how image processing, machine learning and deep learning techniques can be applied for medical diagnostics in several specific health scenarios such as COVID-19, lung cancer, cardiovascular diseases, breast cancer, liver tumor, bone fractures, etc. Also highlighted are the significant issues and concerns regarding the use of AI in healthcare together with other allied areas, such as the Internet of Things (IoT) and medical informatics, to construct a global multidisciplinary forum. Audience The core audience comprises researchers and industry engineers, scientists, radiologists, healthcare professionals, data scientists who work in health informatics, computer vision and medical image analysis.

Machine Learning in Medicine

Machine Learning in Medicine
Author: Ayman El-Baz,Jasjit S. Suri
Publsiher: CRC Press
Total Pages: 312
Release: 2021-08-04
ISBN: 1351588745
Category: Computers
Language: EN, FR, DE, ES & NL

Machine Learning in Medicine Book Excerpt:

Machine Learning in Medicine covers the state-of-the-art techniques of machine learning and their applications in the medical field. It presents several computer-aided diagnosis (CAD) systems, which have played an important role in the diagnosis of several diseases in the past decade, e.g., cancer detection, resulting in the development of several successful systems. New developments in machine learning may make it possible in the near future to develop machines that are capable of completely performing tasks that currently cannot be completed without human aid, especially in the medical field. This book covers such machines, including convolutional neural networks (CNNs) with different activation functions for small- to medium-size biomedical datasets, detection of abnormal activities stemming from cognitive decline, thermal dose modelling for thermal ablative cancer treatments, dermatological machine learning clinical decision support systems, artificial intelligence-powered ultrasound for diagnosis, practical challenges with possible solutions for machine learning in medical imaging, epilepsy diagnosis from structural MRI, Alzheimer's disease diagnosis, classification of left ventricular hypertrophy, and intelligent medical language understanding. This book will help to advance scientific research within the broad field of machine learning in the medical field. It focuses on major trends and challenges in this area and presents work aimed at identifying new techniques and their use in biomedical analysis, including extensive references at the end of each chapter.

Applications of Artificial Intelligence in Medical Imaging

Applications of Artificial Intelligence in Medical Imaging
Author: Abdulhamit Subasi
Publsiher: Academic Press
Total Pages: 400
Release: 2022-11-15
ISBN: 9780443184505
Category: Computers
Language: EN, FR, DE, ES & NL

Applications of Artificial Intelligence in Medical Imaging Book Excerpt:

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