The use of deep learning in mapping and diagnosis of cancers

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Publisher : Frontiers Media SA
ISBN 13 : 2832511694
Total Pages : 228 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis The use of deep learning in mapping and diagnosis of cancers by : Fu Wang

Download or read book The use of deep learning in mapping and diagnosis of cancers written by Fu Wang and published by Frontiers Media SA. This book was released on 2023-01-18 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Deep Learning for Cancer Diagnosis

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Publisher : Springer Nature
ISBN 13 : 9811563217
Total Pages : 311 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Deep Learning for Cancer Diagnosis by : Utku Kose

Download or read book Deep Learning for Cancer Diagnosis written by Utku Kose and published by Springer Nature. This book was released on 2020-09-12 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores various applications of deep learning to the diagnosis of cancer,while also outlining the future face of deep learning-assisted cancer diagnostics. As is commonly known, artificial intelligence has paved the way for countless new solutions in the field of medicine. In this context, deep learning is a recent and remarkable sub-field, which can effectively cope with huge amounts of data and deliver more accurate results. As a vital research area, medical diagnosis is among those in which deep learning-oriented solutions are often employed. Accordingly, the objective of this book is to highlight recent advanced applications of deep learning for diagnosing different types of cancer. The target audience includes scientists, experts, MSc and PhD students, postdocs, and anyone interested in the subjects discussed. The book can be used as a reference work to support courses on artificial intelligence, medical and biomedicaleducation.

Deep Learning in Cancer Diagnostics

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Publisher : Springer Nature
ISBN 13 : 9811989370
Total Pages : 41 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Deep Learning in Cancer Diagnostics by : Mohd Hafiz Arzmi

Download or read book Deep Learning in Cancer Diagnostics written by Mohd Hafiz Arzmi and published by Springer Nature. This book was released on 2023-01-18 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer is the leading cause of mortality in most, if not all, countries around the globe. It is worth noting that the World Health Organisation (WHO) in 2019 estimated that cancer is the primary or secondary leading cause of death in 112 of 183 countries for individuals less than 70 years old, which is alarming. In addition, cancer affects socioeconomic development as well. The diagnostics of cancer are often carried out by medical experts through medical imaging; nevertheless, it is not without misdiagnosis owing to a myriad of reasons. With the advancement of technology and computing power, the use of state-of-the-art computational methods for the accurate diagnosis of cancer is no longer far-fetched. In this brief, the diagnosis of four types of common cancers, i.e., breast, lung, oral and skin, are evaluated with different state-of-the-art feature-based transfer learning models. It is expected that the findings in this book are insightful to various stakeholders in the diagnosis of cancer. ​

Current Applications of Deep Learning in Cancer Diagnostics

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Publisher : CRC Press
ISBN 13 : 1000836150
Total Pages : 189 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Current Applications of Deep Learning in Cancer Diagnostics by : Jyotismita Chaki

Download or read book Current Applications of Deep Learning in Cancer Diagnostics written by Jyotismita Chaki and published by CRC Press. This book was released on 2023-02-22 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines deep learning-based approaches in the field of cancer diagnostics, as well as pre-processing techniques, which are essential to cancer diagnostics. Topics include introduction to current applications of deep learning in cancer diagnostics, pre-processing of cancer data using deep learning, review of deep learning techniques in oncology, overview of advanced deep learning techniques in cancer diagnostics, prediction of cancer susceptibility using deep learning techniques, prediction of cancer reoccurrence using deep learning techniques, deep learning techniques to predict the grading of human cancer, different human cancer detection using deep learning techniques, prediction of cancer survival using deep learning techniques, complexity in the use of deep learning in cancer diagnostics, and challenges and future scopes of deep learning techniques in oncology.

Advanced Machine Learning Approaches in Cancer Prognosis

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Publisher : Springer Nature
ISBN 13 : 3030719758
Total Pages : 461 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Advanced Machine Learning Approaches in Cancer Prognosis by : Janmenjoy Nayak

Download or read book Advanced Machine Learning Approaches in Cancer Prognosis written by Janmenjoy Nayak and published by Springer Nature. This book was released on 2021-05-29 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic, and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learning have proved its vast range of significance and, provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D. students, postdocs, and anyone interested in the subjects discussed.

Machine and Deep Learning in Oncology, Medical Physics and Radiology

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Author :
Publisher : Springer Nature
ISBN 13 : 3030830470
Total Pages : 514 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Machine and Deep Learning in Oncology, Medical Physics and Radiology by : Issam El Naqa

Download or read book Machine and Deep Learning in Oncology, Medical Physics and Radiology written by Issam El Naqa and published by Springer Nature. This book was released on 2022-02-02 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, now in an extensively revised and updated second edition, provides a comprehensive overview of both machine learning and deep learning and their role in oncology, medical physics, and radiology. Readers will find thorough coverage of basic theory, methods, and demonstrative applications in these fields. An introductory section explains machine and deep learning, reviews learning methods, discusses performance evaluation, and examines software tools and data protection. Detailed individual sections are then devoted to the use of machine and deep learning for medical image analysis, treatment planning and delivery, and outcomes modeling and decision support. Resources for varying applications are provided in each chapter, and software code is embedded as appropriate for illustrative purposes. The book will be invaluable for students and residents in medical physics, radiology, and oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.

Application of Deep Learning Methods in Healthcare and Medical Science

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Publisher : CRC Press
ISBN 13 : 1000610683
Total Pages : 325 pages
Book Rating : 4.0/5 (6 download)

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Book Synopsis Application of Deep Learning Methods in Healthcare and Medical Science by : Rohit Tanwar

Download or read book Application of Deep Learning Methods in Healthcare and Medical Science written by Rohit Tanwar and published by CRC Press. This book was released on 2023-01-12 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume provides a wealth of up-to-date information on developments and applications of deep learning in healthcare and medicine, providing deep insight and understanding of novel applications that address the tough questions of disease diagnosis, prevention, and immunization. The volume looks at applications of deep learning for major medical challenges such as cancer detection and identification, birth asphyxia among neonates, kidney abnormalities, white blood cell segmentation, diabetic retinopathy detection, and Covid-19 diagnosis, prevention, and immunization. The volume discusses applications of deep learning in detection, diagnosis, intensive examination and evaluation, genomic sequencing, convolutional neural networks for image recognition and processing, and more for health issues such as kidney problems, brain tumors, lung damage, and breast cancer. The authors look at ML for brain tumor segmentation, in lung CT scans, in digital X-ray devices, and for logistic and transport systems for effective delivery of healthcare.

Machine Learning with Health Care Perspective

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Publisher : Springer Nature
ISBN 13 : 3030408507
Total Pages : 418 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Machine Learning with Health Care Perspective by : Vishal Jain

Download or read book Machine Learning with Health Care Perspective written by Vishal Jain and published by Springer Nature. This book was released on 2020-03-09 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book introduces a variety of techniques designed to represent, enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. Providing a unique compendium of current and emerging machine learning paradigms for healthcare informatics, it reflects the diversity, complexity, and the depth and breadth of this multi-disciplinary area. Further, it describes techniques for applying machine learning within organizations and explains how to evaluate the efficacy, suitability, and efficiency of such applications. Featuring illustrative case studies, including how chronic disease is being redefined through patient-led data learning, the book offers a guided tour of machine learning algorithms, architecture design, and applications of learning in healthcare challenges.

Cancer Prediction for Industrial IoT 4.0

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Publisher : CRC Press
ISBN 13 : 1000508587
Total Pages : 217 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Cancer Prediction for Industrial IoT 4.0 by : Meenu Gupta

Download or read book Cancer Prediction for Industrial IoT 4.0 written by Meenu Gupta and published by CRC Press. This book was released on 2021-12-31 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cancer Prediction for Industrial IoT 4.0: A Machine Learning Perspective explores various cancers using Artificial Intelligence techniques. It presents the rapid advancement in the existing prediction models by applying Machine Learning techniques. Several applications of Machine Learning in different cancer prediction and treatment options are discussed, including specific ideas, tools and practices most applicable to product/service development and innovation opportunities. The wide variety of topics covered offers readers multiple perspectives on various disciplines. Features • Covers the fundamentals, history, reality and challenges of cancer • Presents concepts and analysis of different cancers in humans • Discusses Machine Learning-based deep learning and data mining concepts in the prediction of cancer • Offers real-world examples of cancer prediction • Reviews strategies and tools used in cancer prediction • Explores the future prospects in cancer prediction and treatment Readers will learn the fundamental concepts and analysis of cancer prediction and treatment, including how to apply emerging technologies such as Machine Learning into practice to tackle challenges in domains/fields of cancer with real-world scenarios. Hands-on chapters contributed by academicians and other professionals from reputed organizations provide and describe frameworks, applications, best practices and case studies on emerging cancer treatment and predictions. This book will be a vital resource to graduate students, data scientists, Machine Learning researchers, medical professionals and analytics managers.

Artificial intelligence: A step forward in biomarker discovery and integration towards improved cancer diagnosis and treatment

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Publisher : Frontiers Media SA
ISBN 13 : 2832521800
Total Pages : 112 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Artificial intelligence: A step forward in biomarker discovery and integration towards improved cancer diagnosis and treatment by : Mónica Hebe Vazquez-Levin

Download or read book Artificial intelligence: A step forward in biomarker discovery and integration towards improved cancer diagnosis and treatment written by Mónica Hebe Vazquez-Levin and published by Frontiers Media SA. This book was released on 2023-04-26 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning in Radiation Oncology

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Publisher : Springer
ISBN 13 : 3319183052
Total Pages : 336 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Machine Learning in Radiation Oncology by : Issam El Naqa

Download or read book Machine Learning in Radiation Oncology written by Issam El Naqa and published by Springer. This book was released on 2015-06-19 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: ​This book provides a complete overview of the role of machine learning in radiation oncology and medical physics, covering basic theory, methods, and a variety of applications in medical physics and radiotherapy. An introductory section explains machine learning, reviews supervised and unsupervised learning methods, discusses performance evaluation, and summarizes potential applications in radiation oncology. Detailed individual sections are then devoted to the use of machine learning in quality assurance; computer-aided detection, including treatment planning and contouring; image-guided radiotherapy; respiratory motion management; and treatment response modeling and outcome prediction. The book will be invaluable for students and residents in medical physics and radiation oncology and will also appeal to more experienced practitioners and researchers and members of applied machine learning communities.

Handbook of Deep Learning in Biomedical Engineering and Health Informatics

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Publisher : CRC Press
ISBN 13 : 1000370453
Total Pages : 344 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Handbook of Deep Learning in Biomedical Engineering and Health Informatics by : E. Golden Julie

Download or read book Handbook of Deep Learning in Biomedical Engineering and Health Informatics written by E. Golden Julie and published by CRC Press. This book was released on 2021-09-22 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new volume discusses state-of-the-art deep learning techniques and approaches that can be applied in biomedical systems and health informatics. Deep learning in the biomedical field is an effective method of collecting and analyzing data that can be used for the accurate diagnosis of disease. This volume delves into a variety of applications, techniques, algorithms, platforms, and tools used in this area, such as image segmentation, classification, registration, and computer-aided analysis. The editors proceed on the principle that accurate diagnosis of disease depends on image acquisition and interpretation. There are many methods to get high resolution radiological images, but we are still lacking in automated image interpretation. Currently deep learning techniques are providing a feasible solution for automatic diagnosis of disease with good accuracy. Analyzing clinical data using deep learning techniques enables clinicians to diagnose diseases at an early stage and treat patients more effectively. Chapters explore such approaches as deep learning algorithms, convolutional neural networks and recurrent neural network architecture, image stitching techniques, deep RNN architectures, and more. This volume also depicts how deep learning techniques can be applied for medical diagnostics of several specific health scenarios, such as cancer, COVID-19, acute neurocutaneous syndrome, cardiovascular and neuro diseases, skin lesions and skin cancer, etc. Key features: Introduces important recent technological advancements in the field Describes the various techniques, platforms, and tools used in biomedical deep learning systems Includes informative case studies that help to explain the new technologies Handbook of Deep Learning in Biomedical Engineering and Health Informatics provides a thorough exploration of biomedical systems applied with deep learning techniques and will provide valuable information for researchers, medical and industry practitioners, academicians, and students.

Ultrasound in Oncology: Application of Big Data and Artificial Intelligence

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Publisher : Frontiers Media SA
ISBN 13 : 288974311X
Total Pages : 129 pages
Book Rating : 4.8/5 (897 download)

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Book Synopsis Ultrasound in Oncology: Application of Big Data and Artificial Intelligence by : Hui-Xiong Xu

Download or read book Ultrasound in Oncology: Application of Big Data and Artificial Intelligence written by Hui-Xiong Xu and published by Frontiers Media SA. This book was released on 2022-02-09 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Brain Tumor MRI Image Segmentation Using Deep Learning Techniques

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Publisher : Academic Press
ISBN 13 : 0323983952
Total Pages : 260 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Brain Tumor MRI Image Segmentation Using Deep Learning Techniques by : Jyotismita Chaki

Download or read book Brain Tumor MRI Image Segmentation Using Deep Learning Techniques written by Jyotismita Chaki and published by Academic Press. This book was released on 2021-11-27 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain Tumor MRI Image Segmentation Using Deep Learning Techniques offers a description of deep learning approaches used for the segmentation of brain tumors. The book demonstrates core concepts of deep learning algorithms by using diagrams, data tables and examples to illustrate brain tumor segmentation. After introducing basic concepts of deep learning-based brain tumor segmentation, sections cover techniques for modeling, segmentation and properties. A focus is placed on the application of different types of convolutional neural networks, like single path, multi path, fully convolutional network, cascade convolutional neural networks, Long Short-Term Memory - Recurrent Neural Network and Gated Recurrent Units, and more. The book also highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in brain tumor segmentation. Provides readers with an understanding of deep learning-based approaches in the field of brain tumor segmentation, including preprocessing techniques Integrates recent advancements in the field, including the transformation of low-resolution brain tumor images into super-resolution images using deep learning-based methods, single path Convolutional Neural Network based brain tumor segmentation, and much more Includes coverage of Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN), Gated Recurrent Units (GRU) based Recurrent Neural Network (RNN), Generative Adversarial Networks (GAN), Auto Encoder based brain tumor segmentation, and Ensemble deep learning Model based brain tumor segmentation Covers research Issues and the future of deep learning-based brain tumor segmentation

Soft Computing for Problem Solving

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Publisher : Springer
ISBN 13 : 9811315957
Total Pages : 991 pages
Book Rating : 4.8/5 (113 download)

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Book Synopsis Soft Computing for Problem Solving by : Jagdish Chand Bansal

Download or read book Soft Computing for Problem Solving written by Jagdish Chand Bansal and published by Springer. This book was released on 2018-10-30 with total page 991 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume book presents outcomes of the 7th International Conference on Soft Computing for Problem Solving, SocProS 2017. This conference is a joint technical collaboration between the Soft Computing Research Society, Liverpool Hope University (UK), the Indian Institute of Technology Roorkee, the South Asian University New Delhi and the National Institute of Technology Silchar, and brings together researchers, engineers and practitioners to discuss thought-provoking developments and challenges in order to select potential future directions The book presents the latest advances and innovations in the interdisciplinary areas of soft computing, including original research papers in the areas including, but not limited to, algorithms (artificial immune systems, artificial neural networks, genetic algorithms, genetic programming, and particle swarm optimization) and applications (control systems, data mining and clustering, finance, weather forecasting, game theory, business and forecasting applications). It is a valuable resource for both young and experienced researchers dealing with complex and intricate real-world problems for which finding a solution by traditional methods is a difficult task.

Artificial Intelligence in Breast Cancer Early Detection and Diagnosis

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Publisher : Springer Nature
ISBN 13 : 3030592081
Total Pages : 107 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Artificial Intelligence in Breast Cancer Early Detection and Diagnosis by : Khalid Shaikh

Download or read book Artificial Intelligence in Breast Cancer Early Detection and Diagnosis written by Khalid Shaikh and published by Springer Nature. This book was released on 2020-12-04 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to next generation smart screening technology for medical image analysis that combines artificial intelligence (AI) techniques with digital screening to develop innovative methods for detecting breast cancer. The authors begin with a discussion of breast cancer, its characteristics and symptoms, and the importance of early screening.They then provide insight on the role of artificial intelligence in global healthcare, screening methods for breast cancer using mammogram, ultrasound, and thermogram images, and the potential benefits of using AI-based systems for clinical screening to more accurately detect, diagnose, and treat breast cancer. Discusses various existing screening methods for breast cancer Presents deep information on artificial intelligence-based screening methods Discusses cancer treatment based on geographical differences and cultural characteristics

Machine Learning and Deep Learning Techniques for Medical Science

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Publisher : CRC Press
ISBN 13 : 1000583368
Total Pages : 351 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Machine Learning and Deep Learning Techniques for Medical Science by : K. Gayathri Devi

Download or read book Machine Learning and Deep Learning Techniques for Medical Science written by K. Gayathri Devi and published by CRC Press. This book was released on 2022-05-11 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of machine learning is growing exponentially into every branch of business and science, including medical science. This book presents the integration of machine learning (ML) and deep learning (DL) algorithms that can be applied in the healthcare sector to reduce the time required by doctors, radiologists, and other medical professionals for analyzing, predicting, and diagnosing the conditions with accurate results. The book offers important key aspects in the development and implementation of ML and DL approaches toward developing prediction tools and models and improving medical diagnosis. The contributors explore the recent trends, innovations, challenges, and solutions, as well as case studies of the applications of ML and DL in intelligent system-based disease diagnosis. The chapters also highlight the basics and the need for applying mathematical aspects with reference to the development of new medical models. Authors also explore ML and DL in relation to artificial intelligence (AI) prediction tools, the discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, and pattern recognition approaches to functional magnetic resonance imaging images. This book is for students and researchers of computer science and engineering, electronics and communication engineering, and information technology; for biomedical engineering researchers, academicians, and educators; and for students and professionals in other areas of the healthcare sector. Presents key aspects in the development and the implementation of ML and DL approaches toward developing prediction tools, models, and improving medical diagnosis Discusses the recent trends, innovations, challenges, solutions, and applications of intelligent system-based disease diagnosis Examines DL theories, models, and tools to enhance health information systems Explores ML and DL in relation to AI prediction tools, discovery of drugs, neuroscience, and diagnosis in multiple imaging modalities Dr. K. Gayathri Devi is a Professor at the Department of Electronics and Communication Engineering, Dr. N.G.P Institute of Technology, Tamil Nadu, India. Dr. Kishore Balasubramanian is an Assistant Professor (Senior Scale) at the Department of EEE at Dr. Mahalingam College of Engineering & Technology, Tamil Nadu, India. Dr. Le Anh Ngoc is a Director of Swinburne Innovation Space and Professor in Swinburne University of Technology (Vietnam).