Machine Learning In Computer Aided Diagnosis Medical Imaging Intelligence And Analysis
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Machine Learning In Computer Aided Diagnosis Medical Imaging Intelligence And Analysis
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Author : Suzuki, Kenji
language : en
Publisher: IGI Global
Release Date : 2012-01-31
Machine Learning In Computer Aided Diagnosis Medical Imaging Intelligence And Analysis written by Suzuki, Kenji and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-31 with Computers categories.
"This book provides a comprehensive overview of machine learning research and technology in medical decision-making based on medical images"--Provided by publisher.
Artificial Intelligence In Decision Support Systems For Diagnosis In Medical Imaging
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Author : Kenji Suzuki
language : en
Publisher: Springer
Release Date : 2018-01-09
Artificial Intelligence In Decision Support Systems For Diagnosis In Medical Imaging written by Kenji Suzuki and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-09 with Technology & Engineering categories.
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.
Computer Aided Detection Of Architectural Distortion In Prior Mammograms Of Interval Cancer
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Author : Shantanu Banik
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Computer Aided Detection Of Architectural Distortion In Prior Mammograms Of Interval Cancer written by Shantanu Banik and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Technology & Engineering categories.
Architectural distortion is an important and early sign of breast cancer, but because of its subtlety, it is a common cause of false-negative findings on screening mammograms. Screening mammograms obtained prior to the detection of cancer could contain subtle signs of early stages of breast cancer, in particular, architectural distortion. This book presents image processing and pattern recognition techniques to detect architectural distortion in prior mammograms of interval-cancer cases. The methods are based upon Gabor filters, phase portrait analysis, procedures for the analysis of the angular spread of power, fractal analysis, Laws' texture energy measures derived from geometrically transformed regions of interest (ROIs), and Haralick's texture features. With Gabor filters and phase-portrait analysis, 4,224 ROIs were automatically obtained from 106 prior mammograms of 56 interval-cancer cases, including 301 true-positive ROIs related to architectural distortion, and from 52 mammograms of 13 normal cases. For each ROI, the fractal dimension, the entropy of the angular spread of power, 10 Laws' texture energy measures, and Haralick's 14 texture features were computed. The areas under the receiver operating characteristic (ROC) curves obtained using the features selected by stepwise logistic regression and the leave-one-image-out method are 0.77 with the Bayesian classifier, 0.76 with Fisher linear discriminant analysis, and 0.79 with a neural network classifier. Free-response ROC analysis indicated sensitivities of 0.80 and 0.90 at 5.7 and 8.8 false positives (FPs) per image, respectively, with the Bayesian classifier and the leave-one-image-out method. The present study has demonstrated the ability to detect early signs of breast cancer 15 months ahead of the time of clinical diagnosis, on the average, for interval-cancer cases, with a sensitivity of 0.8 at 5.7 FP/image. The presented computer-aided detection techniques, dedicated to accurate detection and localization of architectural distortion, could lead to efficient detection of early and subtle signs of breast cancer at pre-mass-formation stages. Table of Contents: Introduction / Detection of Early Signs of Breast Cancer / Detection and Analysis of Oriented Patterns / Detection of Potential Sites of Architectural Distortion / Experimental Set Up and Datasets / Feature Selection and Pattern Classification / Analysis of Oriented Patterns Related to Architectural Distortion / Detection of Architectural Distortion in Prior Mammograms / Concluding Remarks
Machine Learning And Deep Learning Techniques For Medical Image Recognition
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Author : Ben Othman Soufiene
language : en
Publisher: CRC Press
Release Date : 2023-12-01
Machine Learning And Deep Learning Techniques For Medical Image Recognition written by Ben Othman Soufiene and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-01 with Technology & Engineering categories.
Machine Learning and Deep Learning Techniques for Medical Image Recognition comprehensively reviews deep learning-based algorithms in medical image analysis problems including medical image processing. It includes a detailed review of deep learning approaches for semantic object detection and segmentation in medical image computing and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks with the theory and varied selection of techniques for semantic segmentation using deep learning principles in medical imaging supported by practical examples. Features: Offers important key aspects in the development and implementation of machine learning and deep learning approaches toward developing prediction tools and models and improving medical diagnosis Teaches how machine learning and deep learning algorithms are applied to a broad range of application areas, including chest X-ray, breast computer-aided detection, lung and chest, microscopy, and pathology Covers common research problems in medical image analysis and their challenges Focuses on aspects of deep learning and machine learning for combating COVID-19 Includes pertinent case studies This book is aimed at researchers and graduate students in computer engineering, artificial intelligence and machine learning, and biomedical imaging.
Big Data Management In Sensing
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Author : Renny Fernandez
language : en
Publisher: CRC Press
Release Date : 2022-09-01
Big Data Management In Sensing written by Renny Fernandez and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-01 with Science categories.
The book is centrally focused on human computer Interaction and how sensors within small and wide groups of Nano-robots employ Deep Learning for applications in industry. It covers a wide array of topics that are useful for researchers and students to gain knowledge about AI and sensors in nanobots. Furthermore, the book explores Deep Learning approaches to enhance the accuracy of AI systems applied in medical robotics for surgical techniques. Secondly, we plan to explore bio-nano-robotics, which is a field in nano-robotics, that deals with automatic intelligence handling, self-assembly and replication, information processing and programmability.
Deep Learning For Smart Healthcare
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Author : K. Murugeswari
language : en
Publisher: CRC Press
Release Date : 2024-05-15
Deep Learning For Smart Healthcare written by K. Murugeswari and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-15 with Medical categories.
Deep learning can provide more accurate results compared to machine learning. It uses layered algorithmic architecture to analyze data. It produces more accurate results since learning from previous results enhances its ability. The multi-layered nature of deep learning systems has the potential to classify subtle abnormalities in medical images, clustering patients with similar characteristics into risk-based cohorts, or highlighting relationships between symptoms and outcomes within vast quantities of unstructured data. Exploring this potential, Deep Learning for Smart Healthcare: Trends, Challenges and Applications is a reference work for researchers and academicians who are seeking new ways to apply deep learning algorithms in healthcare, including medical imaging and healthcare data analytics. It covers how deep learning can analyze a patient’s medical history efficiently to aid in recommending drugs and dosages. It discusses how deep learning can be applied to CT scans, MRI scans and ECGs to diagnose diseases. Other deep learning applications explored are extending the scope of patient record management, pain assessment, new drug design and managing the clinical trial process. Bringing together a wide range of research domains, this book can help to develop breakthrough applications for improving healthcare management and patient outcomes.
Emerging Developments And Practices In Oncology
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Author : El Naqa, Issam
language : en
Publisher: IGI Global
Release Date : 2018-02-09
Emerging Developments And Practices In Oncology written by El Naqa, Issam and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-09 with Medical categories.
Cancer is a leading cause of death that affects numerous people at every age and their relatives. In recent years, there has been a tremendous advancement in imaging and biotechnology technologies and techniques for aiding in the detection, diagnosis, and treatment of cancer. Emerging Developments and Practices in Oncology provides research on recent advances in oncology aiming to improve early detection and personalized treatment of cancer. While highlighting applied methods of therapy, such as body radiotherapy, chemoradiotherapy, and immunotherapy, readers learn about the transforming approach to oncology in modern medicine and new technologies used to diagnose and treat cancer. This book is an important resource for medical trainees, graduate students, active practitioners, researchers, and clinical scientists seeking current research on oncology trends and applications.
Big Data Analytics
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Author : Sanjay Madria
language : en
Publisher: Springer Nature
Release Date : 2019-12-12
Big Data Analytics written by Sanjay Madria and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-12 with Computers categories.
This book constitutes the refereed proceedings of the 7th International Conference on Big Data analytics, BDA 2019, held in Ahmedabad, India, in December 2019. The 25 papers presented in this volume were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections named: big data analytics: vision and perspectives; search and information extraction; predictive analytics in medical and agricultural domains; graph analytics; pattern mining; and machine learning.
Proceedings Of 2021 International Conference On Medical Imaging And Computer Aided Diagnosis Micad 2021
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Author : Ruidan Su
language : en
Publisher: Springer Nature
Release Date : 2021-08-14
Proceedings Of 2021 International Conference On Medical Imaging And Computer Aided Diagnosis Micad 2021 written by Ruidan Su and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-14 with Technology & Engineering categories.
This book covers virtually all aspects of image formation in medical imaging, including systems based on ionizing radiation (x-rays, gamma rays) and non-ionizing techniques (ultrasound, optical, thermal, magnetic resonance, and magnetic particle imaging) alike. In addition, it discusses the development and application of computer-aided detection and diagnosis (CAD) systems in medical imaging. Also there will be a special track on computer-aided diagnosis on COVID-19 by CT and X-rays images. Given its coverage, the book provides both a forum and valuable resource for researchers involved in image formation, experimental methods, image performance, segmentation, pattern recognition, feature extraction, classifier design, machine learning / deep learning, radiomics, CAD workstation design, human–computer interaction, databases, and performance evaluation.
Proceedings Of 2024 International Conference On Medical Imaging And Computer Aided Diagnosis Micad 2024
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Author : Ruidan Su
language : en
Publisher: Springer Nature
Release Date : 2025-04-03
Proceedings Of 2024 International Conference On Medical Imaging And Computer Aided Diagnosis Micad 2024 written by Ruidan Su and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-03 with Computers categories.
This book aims to provide a collaborative platform for leading technology minds to exchange insights, foster interdisciplinary dialogue, and propel advancements in both medical imaging and computer-aided diagnosis. As technology evolves, a plethora of state-of-the-art human imaging devices have made remarkable strides in the medical field, transforming diagnostic and treatment standards. Concurrently, there is a growing emphasis on extracting and deciphering extensive information from medical images, spurring the demand for innovative solutions. The fusion of digital image processing and computer vision technologies has paved the way for computer-aided diagnosis (CAD), a pivotal player in disease analysis. This conference extends a warm invitation to researchers, scholars, engineers, scientists, industry leaders, and graduate students active in these fields. Through diverse participation formats, including compelling poster presentations and enlightening oral sessions, attendees will gain profound insights into the intricate interplay between these realms. This book showcases the latest technological breakthroughs, forging valuable connections and envisioning future applications.