Neuro Fuzzy Pattern Recognition For Mri Problem

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Neuro Fuzzy Pattern Recognition

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Author : Horst Bunke
language : en
Publisher: World Scientific
Release Date : 2000

Neuro Fuzzy Pattern Recognition written by Horst Bunke and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Computers categories.

Neural networks and fuzzy techniques are among the most promising approaches to pattern recognition. Neuro-fuzzy systems aim at combining the advantages of the two paradigms. This book is a collection of papers describing state-of-the-art work in this emerging field. It covers topics such as feature selection, classification, classifier training, and clustering. Also included are applications of neuro-fuzzy systems in speech recognition, land mine detection, medical image analysis, and autonomous vehicle control. The intended audience includes graduate students in computer science and related fields, as well as researchers at academic institutions and in industry.

Neuro Fuzzy Pattern Recognition For Mri Problem

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Author : Chee Wai Quah
language : en
Publisher:
Release Date : 2007

Neuro Fuzzy Pattern Recognition For Mri Problem written by Chee Wai Quah and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Fuzzy logic categories.

Pattern Recognition And Signal Analysis In Medical Imaging

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Author : Anke Meyer-Baese
language : en
Publisher: Elsevier
Release Date : 2003-12-17

Pattern Recognition And Signal Analysis In Medical Imaging written by Anke Meyer-Baese and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-12-17 with Computers categories.

Medical Imaging has become one of the most important visualization and interpretation methods in biology and medecine over the past decade. This time has witnessed a tremendous development of new, powerful instruments for detecting, storing, transmitting, analyzing, and displaying medical images. This has led to a huge growth in the application of digital processing techniques for solving medical problems. Design, implementation, and validation of complex medical systems requires a tight interdisciplinary collaboration between physicians and engineers because poor image quality leads to problematic feature extraction, analysis, and recognition in medical application. Therefore, much of the research done today is geared towards improvement of imperfect image material. This important book by academic authority Anke Meyer-Baese compiles, organizes and explains a complete range of proven and cutting-edge methods, which are playing a leading role in the improvement of image quality, analysis and interpretation in modern medical imaging. These methods offer fresh tools of hope for physicians investigating a vast number of medical problems for which classical methods prove insufficient.*Essential tool for serious students and professionals working with Medical Imaging

Pattern Recognition And Signal Analysis In Medical Imaging

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Author : Anke Meyer-Baese
language : en
Publisher: Elsevier
Release Date : 2014-03-21

Pattern Recognition And Signal Analysis In Medical Imaging written by Anke Meyer-Baese and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-21 with Technology & Engineering categories.

Medical imaging is one of the heaviest funded biomedical engineering research areas. The second edition of Pattern Recognition and Signal Analysis in Medical Imaging brings sharp focus to the development of integrated systems for use in the clinical sector, enabling both imaging and the automatic assessment of the resultant data. Since the first edition, there has been tremendous development of new, powerful technologies for detecting, storing, transmitting, analyzing, and displaying medical images. Computer-aided analytical techniques, coupled with a continuing need to derive more information from medical images, has led to a growing application of digital processing techniques in cancer detection as well as elsewhere in medicine. This book is an essential tool for students and professionals, compiling and explaining proven and cutting-edge methods in pattern recognition for medical imaging. - New edition has been expanded to cover signal analysis, which was only superficially covered in the first edition - New chapters cover Cluster Validity Techniques, Computer-Aided Diagnosis Systems in Breast MRI, Spatio-Temporal Models in Functional, Contrast-Enhanced and Perfusion Cardiovascular MRI - Gives readers an unparalleled insight into the latest pattern recognition and signal analysis technologies, modeling, and applications

Deep Learning For Chest Radiographs

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Author : Yashvi Chandola
language : en
Publisher: Elsevier
Release Date : 2021-07-16

Deep Learning For Chest Radiographs written by Yashvi Chandola and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-16 with Computers categories.

Deep Learning for Chest Radiographs enumerates different strategies implemented by the authors for designing an efficient convolution neural network-based computer-aided classification (CAC) system for binary classification of chest radiographs into "Normal" and "Pneumonia." Pneumonia is an infectious disease mostly caused by a bacteria or a virus. The prime targets of this infectious disease are children below the age of 5 and adults above the age of 65, mostly due to their poor immunity and lower rates of recovery. Globally, pneumonia has prevalent footprints and kills more children as compared to any other immunity-based disease, causing up to 15% of child deaths per year, especially in developing countries. Out of all the available imaging modalities, such as computed tomography, radiography or X-ray, magnetic resonance imaging, ultrasound, and so on, chest radiographs are most widely used for differential diagnosis between Normal and Pneumonia. In the CAC system designs implemented in this book, a total of 200 chest radiograph images consisting of 100 Normal images and 100 Pneumonia images have been used. These chest radiographs are augmented using geometric transformations, such as rotation, translation, and flipping, to increase the size of the dataset for efficient training of the Convolutional Neural Networks (CNNs). A total of 12 experiments were conducted for the binary classification of chest radiographs into Normal and Pneumonia. It also includes in-depth implementation strategies of exhaustive experimentation carried out using transfer learning-based approaches with decision fusion, deep feature extraction, feature selection, feature dimensionality reduction, and machine learning-based classifiers for implementation of end-to-end CNN-based CAC system designs, lightweight CNN-based CAC system designs, and hybrid CAC system designs for chest radiographs. This book is a valuable resource for academicians, researchers, clinicians, postgraduate and graduate students in medical imaging, CAC, computer-aided diagnosis, computer science and engineering, electrical and electronics engineering, biomedical engineering, bioinformatics, bioengineering, and professionals from the IT industry. - Provides insights into the theory, algorithms, implementation, and application of deep-learning techniques for medical images such as transfer learning using pretrained CNNs, series networks, directed acyclic graph networks, lightweight CNN models, deep feature extraction, and conventional machine learning approaches for feature selection, feature dimensionality reduction, and classification using support vector machine, neuro-fuzzy classifiers - Covers the various augmentation techniques that can be used with medical images and the CNN-based CAC system designs for binary classification of medical images focusing on chest radiographs - Investigates the development of an optimal CAC system design with deep feature extraction and classification of chest radiographs by comparing the performance of 12 different CAC system designs

Hybrid Intelligent Systems In Control Pattern Recognition And Medicine

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Author : Oscar Castillo
language : en
Publisher: Springer Nature
Release Date : 2019-11-23

Hybrid Intelligent Systems In Control Pattern Recognition And Medicine written by Oscar Castillo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-23 with Technology & Engineering categories.

This book describes the latest advances in fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations, and their applications in areas such as: intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction, and optimization of complex problems. The book is divided into five main parts. The first part proposes new concepts and algorithms based on type-1 and type-2 fuzzy logic and their applications; the second explores new concepts and algorithms in neural networks and fuzzy logic applied to recognition. The third part examines the theory and practice of meta-heuristics in various areas of application, while the fourth highlights diverse applications of fuzzy logic, neural networks and hybrid intelligent systems in medical contexts. Finally, the fifth part focuses on applications of fuzzy logic, neural networks and meta-heuristics to robotics problems.

Advances In Fuzzy Based Internet Of Medical Things Iomt

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Author : Satya Prakash Yadav
language : en
Publisher: John Wiley & Sons
Release Date : 2024-04-16

Advances In Fuzzy Based Internet Of Medical Things Iomt written by Satya Prakash Yadav and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-16 with Computers categories.

ADVANCES IN FUZZY-BASED INTERNET OF MEDICAL THINGS (IOMT) This book explores the latest trends, transitions, and advancements of the Internet of Medical Things whose integration through cloud-hosted software applications adds required intelligence from tools such as medical instruments, scanners, and appliances, enabling fuzzy logic to help medical professionals establish linguistic concepts in deciding diagnosis and prognosis. The main goal of the book is to strengthen medical professionals and caregivers by providing methods for achieving fuzzy logic-based health diagnosis and medication. The health condition and various physical parameters of humans, such as heartbeat rate, sugar level, blood pressure, temperature, and oxygen quality, are captured through a host of multifaceted sensors. Additionally, remote health monitoring, medication, and management are being facilitated through a host of ingestible sensors, 5G communication, networked embedded systems, AI models running on cloud servers and edge devices, etc. Furthermore, chronic disease management is another vital domain getting increased attention. The distinct advancements in the fuzzy logic field are useful in various advanced medical care functionalities and facilities. The readers will discover: new and innovative features of health care by using fuzzy logic that raises economic efficiency at macro and micro levels; expounds on fuzzy logic techniques used in medical science; describes the evolution of the fuzzy logic paradigm and how it helps physicians decide on diagnosis and prognosis; uncovers how trust management is dealt with between patients and medical officials to help advance the fuzzy logic field; provides case studies, various technology advancements, and practical aspects on the impacts and challenges of fuzzy-based Internet of Medical Things. Audience The book will be read and used by researchers in artificial intelligence, fuzzy logic, medical professionals, caregivers, health administrators, and policymakers.

Adversarial Deep Generative Techniques For Early Diagnosis Of Neurological Conditions And Mental Health Practises

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Author : Abhishek Kumar
language : en
Publisher: Springer Nature
Release Date : 2025-08-16

Adversarial Deep Generative Techniques For Early Diagnosis Of Neurological Conditions And Mental Health Practises written by Abhishek Kumar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-16 with Computers categories.

This book explores a pioneering exploration of how deep generative models, including generative adversarial networks (GANs) and variational autoencoders (VAEs), renovating early neurological disorder detection. This book is a bridge between computational neuroscience and clinical neurology gaps, providing novel AI-driven methodologies for diagnosing conditions such as Alzheimer’s, Parkinson’s, epilepsy, and neurodevelopmental disorders. With a strong focus on neuroimaging, genomic data analysis, and biomedical informatics, the book equips researchers and practitioners with the tools to improve diagnostic accuracy and decision-making. It includes practical case studies, visual illustrations, and structured methodologies for training and validating deep learning models. Designed for neurologists, radiologists, data scientists, and AI researchers, this book is an essential resource for advancing precision medicine and next-generation healthcare innovation.

Mild Cognitive Impairment Recognition Via Gene Expression Mining And Neuroimaging Techniques

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Author : Mohammad Khosravi
language : en
Publisher: Frontiers Media SA
Release Date : 2022-12-02

Mild Cognitive Impairment Recognition Via Gene Expression Mining And Neuroimaging Techniques written by Mohammad Khosravi and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-02 with Science categories.

High Resolution Neuroimaging

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Author : Ahmet Mesrur Halefoğlu
language : en
Publisher: BoD – Books on Demand
Release Date : 2018-03-14

High Resolution Neuroimaging written by Ahmet Mesrur Halefoğlu and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-14 with Medical categories.

Dr. Ahmet Mesrur Halefoğlu mostly deals with research fields in body imaging and neuroradiology with multidetector computed tomography and high-resolution magnetic resonance imaging. He has served as postdoctoral research fellow at Johns Hopkins Hospital. Currently, he is working as an associate professor of radiology in Istanbul, Turkey. He has more than 50 high-impact-factor publications and has written 3 book chapters. He is a member of Turkish Society of Radiology and European Society of Radiology. During the recent years, there have been major breakthroughs in MRI due to developments in scanner technology and pulse sequencing. These important achievements have led to remarkable improvements in neuroimaging and advanced techniques, including diffusion imaging, diffusion tensor imaging, perfusion imaging, magnetic resonance spectroscopy, and functional MRI. These advanced neuroimaging techniques have enabled us to achieve invaluable insights into tissue microstructure, microvasculature, metabolism, and brain connectivity.