Deep Learning In Biomedical Signal And Medical Imaging
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Deep Learning In Biomedical Signal And Medical Imaging
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Author : Ngangbam Herojit Singh
language : en
Publisher: CRC Press
Release Date : 2024-09-30
Deep Learning In Biomedical Signal And Medical Imaging written by Ngangbam Herojit Singh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-30 with Computers categories.
This book offers detailed information on biomedical imaging using Deep Convolutional Neural Networks (Deep CNN). It focuses on different types of biomedical images to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis and image processing perspectives. Deep Learning in Biomedical Signal and Medical Imaging discusses classification, segmentation, detection, tracking, and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT, and X-RAY, amongst others. It surveys the most recent techniques and approaches in this field, with both broad coverage and enough depth to be of practical use to working professionals. It includes examples of the application of signal and image processing employing Deep CNN to Alzheimer’s, brain tumor, skin cancer, breast cancer, and stroke prediction, as well as ECG and EEG signals. This book offers enough fundamental and technical information on these techniques, approaches, and related problems without overcrowding the reader’s head. It presents the results of the latest investigations in the field of Deep CNN for biomedical data analysis. The techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine the fundamental theory of artificial intelligence (AI), machine learning (ML,) and Deep CNN with practical applications in biology and medicine. Certainly, the list of topics covered in this book is not exhaustive, but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis. The book is written for graduate students, researchers, and professionals in biomedical engineering, electrical engineering, signal process engineering, biomedical imaging, and computer science. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educators who are working in the context of the topics.
Deep Learning In Biomedical Signal And Medical Imaging
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Author : Ngangbam Herojit Singh
language : en
Publisher:
Release Date : 2025
Deep Learning In Biomedical Signal And Medical Imaging written by Ngangbam Herojit Singh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with categories.
"This book offers detailed information on biomedical imaging using Deep Convolutional Neural Networks (Deep CNN). It focuses on different types of biomedical images to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis, and image processing perspectives. Deep Learning in Biomedical Signal and Medical Imaging discusses classification, segmentation, detection, tracking, and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT, and X-RAY, amongst others. It surveys the most recent techniques and approaches in this field, with both broad coverage and enough depth to be of practical use to working professionals. It includes examples of the application of signal and image processing employing Deep CNN to Alzheimer, Brain Tumor, Skin Cancer, Breast Cancer, and stroke prediction, as well as ECG and EEG signals. This book offers enough fundamental and technical information on these techniques, approaches, and related problems without overcrowding the reader's head. It presents the results of the latest investigations in the field of Deep CNN for biomedical data analysis. The techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine the fundamental theory of Artificial Intelligence (AI), Machine Learning (ML,) and Deep CNN with practical applications in Biology and Medicine. Certainly, the list of topics covered in this book is not exhaustive but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis. The book is written for graduate students, researchers, and professionals in biomedical engineering, electrical engineering, signal process engineering, biomedical imaging, and computer science. The specific and innovative solutions covered in this book for both medical and biomedical applications are critical to scientists, researchers, practitioners, professionals, and educators who are working in the context of the topics"--
Diagnostic Biomedical Signal And Image Processing Applications With Deep Learning Methods
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Author : Kemal Polat
language : en
Publisher: Elsevier
Release Date : 2023-04-30
Diagnostic Biomedical Signal And Image Processing Applications With Deep Learning Methods written by Kemal Polat and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-30 with Computers categories.
Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges that are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities. Focusing on solving real medical problems using new deep learning and CNN approaches, this book will appeal to research scholars, graduate students, faculty members, R&D engineers, and biomedical engineers who want to learn how medical signals and images play an important role in the early diagnosis and treatment of diseases. - Investigates novel concepts of deep learning for acquisition of non-invasive biomedical image and signal modalities for different disorders - Explores the implementation of novel deep learning and CNN methodologies and their impact studies that have been tested on different medical case studies - Presents end-to-end CNN architectures for automatic detection of situations where early diagnosis is important - Includes novel methodologies, datasets, design and simulation examples
Deep Learning For Biomedical Image Reconstruction
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Author : Jong Chul Ye
language : en
Publisher: Cambridge University Press
Release Date : 2023-10-12
Deep Learning For Biomedical Image Reconstruction written by Jong Chul Ye and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-12 with Medical categories.
Discover the power of deep neural networks for image reconstruction with this state-of-the-art review of modern theories and applications. The background theory of deep learning is introduced step-by-step, and by incorporating modeling fundamentals this book explains how to implement deep learning in a variety of modalities, including X-ray, CT, MRI and others. Real-world examples demonstrate an interdisciplinary approach to medical image reconstruction processes, featuring numerous imaging applications. Recent clinical studies and innovative research activity in generative models and mathematical theory will inspire the reader towards new frontiers. This book is ideal for graduate students in Electrical or Biomedical Engineering or Medical Physics.
Machine Learning In Bio Signal Analysis And Diagnostic Imaging
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Author : Nilanjan Dey
language : en
Publisher: Academic Press
Release Date : 2018-11-30
Machine Learning In Bio Signal Analysis And Diagnostic Imaging written by Nilanjan Dey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-30 with Science categories.
Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. - Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging - Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining - Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains
Deep Learning In Medical Signal And Image Processing
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Author : Aamir, Muhammad
language : en
Publisher: IGI Global
Release Date : 2025-05-23
Deep Learning In Medical Signal And Image Processing written by Aamir, Muhammad and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-23 with Computers categories.
Deep learning is revolutionizing the analysis of medical signals and images, offering unprecedented advancements in diagnostic accuracy and efficiency. Techniques such as convolutional and recurrent neural networks are transforming the processing of radiological scans, ultrasound images, and ECG readings. By enabling more detailed and precise interpretations, deep learning enhances the ability of healthcare providers to make timely and informed decisions. These innovations are reshaping medical workflows, improving patient outcomes, and paving the way for a future of more reliable and efficient healthcare solutions. Deep Learning in Medical Signal and Image Processing offers a comprehensive examination of deep learning, specifically through convolutional neural networks (CNNs) and recurrent neural networks (RNNs), to medical data. It explores the application of AI in the analysis of medical signals and images. Covering topics such as diagnostic accuracy, enhanced decision-making, and data augmentation techniques, this book is an excellent resource for medical practitioners, clinicians, data scientists, AI researchers, healthcare professionals, engineers, professionals, researchers, scholars, academicians, and more.
Machine Learning And Ai Techniques In Interactive Medical Image Analysis
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Author : Panigrahi, Lipismita
language : en
Publisher: IGI Global
Release Date : 2022-09-16
Machine Learning And Ai Techniques In Interactive Medical Image Analysis written by Panigrahi, Lipismita and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-16 with Medical categories.
The healthcare industry is predominantly moving towards affordable, accessible, and quality health care. All organizations are striving to build communication compatibility among the wide range of devices that have operated independently. Recent developments in electronic devices have boosted the research in the medical imaging field. It incorporates several medical imaging techniques and achieves an important goal for health improvement all over the world. Despite the significant advances in high-resolution medical instruments, physicians cannot always obtain the full amount of information directly from the equipment outputs, and a large amount of data cannot be easily exploited without a computer. Machine Learning and AI Techniques in Interactive Medical Image Analysis discusses how clinical efficiency can be improved by investigating the different types of intelligent techniques and systems to get more reliable and accurate diagnostic conclusions. This book further introduces segmentation techniques to locate suspicious areas in medical images and increase the segmentation accuracy. Covering topics such as computer-aided detection, intelligent techniques, and machine learning, this premier reference source is a dynamic resource for IT specialists, computer scientists, diagnosticians, imaging specialists, medical professionals, hospital administrators, medical students, medical technicians, librarians, researchers, and academicians.
Machine Learning Models And Architectures For Biomedical Signal Processing
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Author : Suman Lata Tripathi
language : en
Publisher: Elsevier
Release Date : 2024-11-05
Machine Learning Models And Architectures For Biomedical Signal Processing written by Suman Lata Tripathi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-05 with Computers categories.
Machine Learning Models and Architectures for Biomedical Signal Processing presents the fundamental concepts of machine learning techniques for bioinformatics in an interactive way. The book investigates how efficient machine and deep learning models can support high-speed processors with reconfigurable architectures like graphic processing units (GPUs), Field programmable gate arrays (FPGAs), or any hybrid system. This great resource will be of interest to researchers working to increase the efficiency of hardware and architecture design for biomedical signal processing and signal processing techniques. - Covers the hardware architecture implementation of machine learning algorithms - Discusses the software implementation approach and the efficient hardware of machine learning application with FPGA - Presents the major design challenges and research potential in machine learning techniques
Signal Processing In Medicine And Biology
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Author : Iyad Obeid
language : en
Publisher: Springer Nature
Release Date : 2020-03-16
Signal Processing In Medicine And Biology written by Iyad Obeid and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-16 with Technology & Engineering categories.
This book covers emerging trends in signal processing research and biomedical engineering, exploring the ways in which signal processing plays a vital role in applications ranging from medical electronics to data mining of electronic medical records. Topics covered include statistical modeling of electroencephalograph data for predicting or detecting seizure, stroke, or Parkinson’s; machine learning methods and their application to biomedical problems, which is often poorly understood, even within the scientific community; signal analysis; medical imaging; and machine learning, data mining, and classification. The book features tutorials and examples of successful applications that will appeal to a wide range of professionals and researchers interested in applications of signal processing, medicine, and biology.
Machine Learning In Medical Imaging
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Author : Chunfeng Lian
language : en
Publisher: Springer Nature
Release Date : 2021-09-25
Machine Learning In Medical Imaging written by Chunfeng Lian and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-25 with Computers categories.
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.