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Computational Intelligence And Image Processing In Medical Applications
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Book Synopsis Computational Intelligence And Image Processing In Medical Applications by : Chi Hau Chen
Download or read book Computational Intelligence And Image Processing In Medical Applications written by Chi Hau Chen and published by World Scientific. This book was released on 2022-05-30 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, there have been significant progress in computational intelligence and image processing with machine learning and deep learning as important components of modern artificial intelligence. All these progresses face challenges in dealing with Covid-19 pandemic for detection and treatment.This comprehensive compendium provides not only updated advances of computational intelligence and image processing in the detection and treatment of Covid-19, but also other medical applications such as in cancer detection and cardiovascular diseases, etc. More traditional approaches such as 2D segmentation and 3D reconstruction are included.The useful reference text is an updated version of the edited title, Computer Vision in Medical Imaging (World Scientific, 2014) and its companion volume, Frontiers of Medical Imaging (World Scientific, 2015). The book is written for engineers, scientists and the medical community to meet the increased challenges in medical applications.
Book Synopsis Computational Intelligence in Medical Imaging by : G. Schaefer
Download or read book Computational Intelligence in Medical Imaging written by G. Schaefer and published by CRC Press. This book was released on 2009-03-24 with total page 504 pages. Available in PDF, EPUB and Kindle. 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.
Book Synopsis Computational Intelligence and Its Applications in Healthcare by : Jitendra Kumar Verma
Download or read book Computational Intelligence and Its Applications in Healthcare written by Jitendra Kumar Verma and published by Academic Press. This book was released on 2020-08-01 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Intelligence and Its Applications in Healthcare presents rapidly growing applications of computational intelligence for healthcare systems, including intelligent synthetic characters, man-machine interface, menu generators, user acceptance analysis, pictures archiving, and communication systems. Computational intelligence is the study of the design of intelligent agents, which are systems that act intelligently: they do what they think are appropriate for their circumstances and goals; they're flexible to changing environments and goals; they learn from experience; and they make appropriate choices given perceptual limitations and finite computation. Computational intelligence paradigms offer many advantages in maintaining and enhancing the field of healthcare. Provides coverage of fuzzy logic, neural networks, evolutionary computation, learning theory, probabilistic methods, telemedicine, and robotics applications Includes coverage of artificial intelligence and biological applications, soft computing, image and signal processing, and genetic algorithms Presents the latest developments in computational methods in healthcare Bridges the gap between obsolete literature and current literature
Book Synopsis Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing by : Rohit Raja
Download or read book Artificial Intelligence and Machine Learning in 2D/3D Medical Image Processing written by Rohit Raja and published by CRC Press. This book was released on 2020-12-22 with total page 215 pages. Available in PDF, EPUB and Kindle. 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
Download or read book Medical Imaging written by K.C. Santosh and published by CRC Press. This book was released on 2019-08-20 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Winner of the "Outstanding Academic Title" recognition by Choice for the 2020 OAT Awards. The Choice OAT Award represents the highest caliber of scholarly titles that have been reviewed by Choice and conveys the extraordinary recognition of the academic community. 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.
Book Synopsis Computational Intelligence Methods for Super-Resolution in Image Processing Applications by : Anand Deshpande
Download or read book Computational Intelligence Methods for Super-Resolution in Image Processing Applications written by Anand Deshpande and published by Springer Nature. This book was released on 2021-05-28 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the application of deep learning techniques within a particularly difficult computational type of computer vision (CV) problem ─ super-resolution (SR). The authors present and discuss ways to apply computational intelligence (CI) methods to SR. The volume also explores the possibility of using different kinds of CV techniques to develop and enhance the tools/processes related to SR. The application areas covered include biomedical engineering, healthcare applications, medicine, histology, and material science. The book will be a valuable reference for anyone concerned with multiple multimodal images, especially professionals working in remote sensing, nanotechnology and immunology at research institutes, healthcare facilities, biotechnology institutions, agribusiness services, veterinary facilities, and universities.
Book Synopsis High-Performance Medical Image Processing by : Sanjay Saxena
Download or read book High-Performance Medical Image Processing written by Sanjay Saxena and published by CRC Press. This book was released on 2022-07-07 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: The processing of medical images in a reasonable timeframe and with high definition is very challenging. This volume helps to meet that challenge by presenting a thorough overview of medical imaging modalities, its processing, high-performance computing, and the need to embed parallelism in medical image processing techniques to achieve efficient and fast results. With contributions from researchers from prestigious laboratories and educational institutions, High-Performance Medical Image Processing provides important information on medical image processing techniques, parallel computing techniques, and embedding parallelism in different image processing techniques. A comprehensive review of parallel algorithms in medical image processing problems is a key feature of this book. The volume presents the relevant theoretical frameworks and the latest empirical research findings in the area and provides detailed descriptions about the diverse high-performance techniques. Topics discussed include parallel computing, multicore architectures and their applications in image processing, machine learning applications, conventional and advanced magnetic resonance imaging methods, hyperspectral image processing, algorithms for segmenting 2D slices for 3D viewing, and more. Case studies, such as on the detection of cancer tumors, expound on the information presented. Key features: Provides descriptions of different medical imaging modalities and their applications Discusses the basics and advanced aspects of parallel computing with different multicore architectures Expounds on the need for embedding data and task parallelism in different medical image processing techniques Presents helpful examples and case studies of the discussed methods This book will be valuable for professionals, researchers, and students working in the field of healthcare engineering, medical imaging technology, applications in machine and deep learning, and more. It is also appropriate for courses in computer engineering, biomedical engineering and electrical engineering based on artificial intelligence, parallel computing, high performance computing, and machine learning and its applications in medical imaging.
Book Synopsis Modern Computational Intelligence Methods for the Interpretation of Medical Images by : Ryszard Tadeusiewicz
Download or read book Modern Computational Intelligence Methods for the Interpretation of Medical Images written by Ryszard Tadeusiewicz and published by Springer Science & Business Media. This book was released on 2008-01-03 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work by two accomplished Polish researchers provides medical technicians and researchers alike with detailed descriptions of up-to-date methods used for computer processing and interpretation of medical images. The broad scope of the book takes in images acquisition, storing with compression, processing, analysis, recognition and also its automatic understanding. The introduction provides a general overview of the computer vision methods designed for medical images.
Book Synopsis Artificial Intelligence in Medical Imaging by : Erik R. Ranschaert
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.
Book Synopsis Advanced Machine Vision Paradigms for Medical Image Analysis by : Tapan K. Gandhi
Download or read book Advanced Machine Vision Paradigms for Medical Image Analysis written by Tapan K. Gandhi and published by Academic Press. This book was released on 2020-08-11 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis
Book Synopsis Signal and Image Processing in Medical Applications by : Amit Kumar
Download or read book Signal and Image Processing in Medical Applications written by Amit Kumar and published by Springer. This book was released on 2016-04-01 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights recent findings on and analyses conducted on signals and images in the area of medicine. The experimental investigations involve a variety of signals and images and their methodologies range from very basic to sophisticated methods. The book explains how signal and image processing methods can be used to detect and forecast abnormalities in an easy-to-follow manner, offering a valuable resource for researchers, engineers, physicians and bioinformatics researchers alike.
Book Synopsis Applications of Artificial Intelligence in Medical Imaging by : Abdulhamit Subasi
Download or read book Applications of Artificial Intelligence in Medical Imaging written by Abdulhamit Subasi and published by Academic Press. This book was released on 2022-11-10 with total page 381 pages. Available in PDF, EPUB and Kindle. 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
Book Synopsis Computer Vision in Medical Imaging by : C H Chen
Download or read book Computer Vision in Medical Imaging written by C H Chen and published by World Scientific. This book was released on 2013-11-18 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: The major progress in computer vision allows us to make extensive use of medical imaging data to provide us better diagnosis, treatment and predication of diseases. Computer vision can exploit texture, shape, contour and prior knowledge along with contextual information from image sequence and provide 3D and 4D information that helps with better human understanding. Many powerful tools have been available through image segmentation, machine learning, pattern classification, tracking, reconstruction to bring much needed quantitative information not easily available by trained human specialists. The aim of the book is for both medical imaging professionals to acquire and interpret the data, and computer vision professionals to provide enhanced medical information by using computer vision techniques. The final objective is to benefit the patients without adding to the already high medical costs. Contents:An Introduction to Computer Vision in Medical Imaging (Chi Hau Chen)Theory and Methodologies:Distribution Matching Approaches to Medical Image Segmentation (Ismail Ben Ayed)Digital Pathology in Medical Imaging (Bikash Sabata, Chukka Srinivas, Pascal Bamford and Gerardo Fernandez)Adaptive Shape Prior Modeling via Online Dictionary Learning (Shaoting Zhang, Yiqiang Zhan, Yan Zhou and Dimitris Metaxas)Feature-Centric Lesion Detection and Retrieval in Thoracic Images (Yang Song, Weidong Cai, Stefan Eberl, Michael J Fulham and David Dagan Feng)A Novel Paradigm for Quantitation from MR Phase (Joseph Dagher)A Multi-Resolution Active Contour Framework for Ultrasound Image Segmentation (Weiming Wang, Jing Qin, Pheng-Ann Heng, Yim-Pan Chui, Liang Li and Bing Nan Li)2D, 3D Reconstructions/Imaging Algorithms, Systems & Sensor Fusion:Model-Based Image Reconstruction in Optoacoustic Tomography (Amir Rosenthal, Daniel Razansky and Vasilis Ntziachristos)The Fusion of Three-Dimensional Quantitative Coronary Angiography and Intracoronary Imaging for Coronary Interventions (Shengxian Tu, Niels R Holm, Johannes P Janssen and Johan H C Reiber)Three-Dimensional Reconstruction Methods in Near-Field Coded Aperture for SPECT Imaging System (Stephen Baoming Hong)Ultrasound Volume Reconstruction based on Direct Frame Interpolation (Sergei Koptenko, Rachel Remlinger, Martin Lachaine, Tony Falco and Ulrich Scheipers)Deconvolution Technique for Enhancing and Classifying the Retinal Images (Uvais A Qidwai and Umair A Qidwai)Medical Ultrasound Digital Signal Processing in the GPU Computing Era (Marcin Lewandowski)Developing Medical Image Processing Algorithms for GPU Assisted Parallel Computation (Mathias Broxvall and Marios Daotis)Specific Image Processing and Computer Vision Methods for Different Imaging Modalities Including IVUS, MRI, etc.:Computer Vision in Interventional Cardiology (Kendall R Waters)Pattern Classification of Brain Diffusion MRI: Application to Schizophrenia Diagnosis (Ali Tabesh, Matthew J Hoptman, Debra D'Angelo and Babak A Ardekani)On Compressed Sensing Reconstruction for Magnetic Resonance Imaging (Benjamin Paul Berman, Sagar Mandava and Ali Bilgin)On Hierarchical Statistical Shape Models with Application to Brain MRI (Juan J Cerrolaza, Arantxa Villanueva and Rafael Cabeza)Advanced PDE-based Methods for Automatic Quantification of Cardiac Function and Scar from Magnetic Resonance Imaging (Durco Turco and Cristiana Corsi)Automated IVUS Segmentation Using Deformable Template Model with Feature Tracking (Prakash Manandhar and Chi Hau Chen) Readership: Researchers, professionals and academics in machine perception/computer vision, pattern recognition/image analysis, nuclear medicine, bioengineering & cardiology. Keywords:Medical Imaging;Computer Vision;Image Segmentation;Machine Learning;3D InformationKey Features:Uses computer vision techniques for medical imaging dataCovers image processing and segmentation algorithms in intravascular ultrasound, PETscan data, MRI dataEmphaisises 3D information extraction from medical imaging data
Download or read book Medical Imaging written by K.C. Santosh and published by CRC Press. This book was released on 2019-08-20 with total page 200 pages. Available in PDF, EPUB and Kindle. 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.
Book Synopsis Advancement of Machine Intelligence in Interactive Medical Image Analysis by : Om Prakash Verma
Download or read book Advancement of Machine Intelligence in Interactive Medical Image Analysis written by Om Prakash Verma and published by Springer Nature. This book was released on 2019-12-11 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book discusses major technical advances and research findings in the field of machine intelligence in medical image analysis. It examines the latest technologies and that have been implemented in clinical practice, such as computational intelligence in computer-aided diagnosis, biological image analysis, and computer-aided surgery and therapy. This book provides insights into the basic science involved in processing, analysing, and utilising all aspects of advanced computational intelligence in medical decision-making based on medical imaging.
Book Synopsis Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging by : Kenji Suzuki
Download or read book Artificial Intelligence in Decision Support Systems for Diagnosis in Medical Imaging written by Kenji Suzuki and published by Springer. This book was released on 2018-01-09 with total page 387 pages. Available in PDF, EPUB and Kindle. 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.
Book Synopsis Medical Image Analysis by : Alejandro Frangi
Download or read book Medical Image Analysis written by Alejandro Frangi and published by Academic Press. This book was released on 2023-09-20 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical Image Analysis presents practical knowledge on medical image computing and analysis as written by top educators and experts. This text is a modern, practical, self-contained reference that conveys a mix of fundamental methodological concepts within different medical domains. Sections cover core representations and properties of digital images and image enhancement techniques, advanced image computing methods (including segmentation, registration, motion and shape analysis), machine learning, how medical image computing (MIC) is used in clinical and medical research, and how to identify alternative strategies and employ software tools to solve typical problems in MIC. Provides an authoritative description of key concepts and methods Includes tutorial-based sections that clearly explain principles and their application to different medical domains Presents a representative selection of topics to match a modern and relevant approach to medical image computing
