Brain Tumor Mri Image Segmentation Using Deep Learning Techniques

Download Brain Tumor Mri Image Segmentation Using Deep Learning Techniques full books in PDF, epub, and Kindle. Read online Brain Tumor Mri Image Segmentation Using Deep Learning Techniques ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Brain Tumor MRI Image Segmentation Using Deep Learning Techniques

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

DOWNLOAD NOW!

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

Brain Tumor MRI Image Segmentation Using Deep Learning Techniques

Author : Jyotismita Chaki
Publisher : Elsevier
ISBN 13 : 0323911714
Total Pages : 258 pages
Book Rating : 4.3/5 (239 download)

DOWNLOAD NOW!

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 Elsevier. This book was released on 2021-12-02 with total page 258 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

Deep Neural Networks for Multimodal Imaging and Biomedical Applications

Author : Suresh, Annamalai
Publisher : IGI Global
ISBN 13 : 1799835928
Total Pages : 294 pages
Book Rating : 4.7/5 (998 download)

DOWNLOAD NOW!

Book Synopsis Deep Neural Networks for Multimodal Imaging and Biomedical Applications by : Suresh, Annamalai

Download or read book Deep Neural Networks for Multimodal Imaging and Biomedical Applications written by Suresh, Annamalai and published by IGI Global. This book was released on 2020-06-26 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of healthcare is seeing a rapid expansion of technological advancement within current medical practices. The implementation of technologies including neural networks, multi-model imaging, genetic algorithms, and soft computing are assisting in predicting and identifying diseases, diagnosing cancer, and the examination of cells. Implementing these biomedical technologies remains a challenge for hospitals worldwide, creating a need for research on the specific applications of these computational techniques. Deep Neural Networks for Multimodal Imaging and Biomedical Applications provides research exploring the theoretical and practical aspects of emerging data computing methods and imaging techniques within healthcare and biomedicine. The publication provides a complete set of information in a single module starting from developing deep neural networks to predicting disease by employing multi-modal imaging. Featuring coverage on a broad range of topics such as prediction models, edge computing, and quantitative measurements, this book is ideally designed for researchers, academicians, physicians, IT consultants, medical software developers, practitioners, policymakers, scholars, and students seeking current research on biomedical advancements and developing computational methods in healthcare.

Brain Tumor Detection Based on Convolutional Neural Network with Neutrosophic Expert Maximum Fuzzy Sure Entropy

Author : Fatih ÖZYURT
Publisher : Infinite Study
ISBN 13 :
Total Pages : 16 pages
Book Rating : 4./5 ( download)

DOWNLOAD NOW!

Book Synopsis Brain Tumor Detection Based on Convolutional Neural Network with Neutrosophic Expert Maximum Fuzzy Sure Entropy by : Fatih ÖZYURT

Download or read book Brain Tumor Detection Based on Convolutional Neural Network with Neutrosophic Expert Maximum Fuzzy Sure Entropy written by Fatih ÖZYURT and published by Infinite Study. This book was released on with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain tumor classification is a challenging task in the field of medical image processing. The present study proposes a hybrid method using Neutrosophy and Convolutional Neural Network (NS-CNN). It aims to classify tumor region areas that are segmented from brain images as benign and malignant. In the first stage, MRI images were segmented using the neutrosophic set – expert maximum fuzzy-sure entropy (NS-EMFSE) approach.

Deep Learning and Data Labeling for Medical Applications

Author : Gustavo Carneiro
Publisher : Springer
ISBN 13 : 3319469762
Total Pages : 289 pages
Book Rating : 4.3/5 (194 download)

DOWNLOAD NOW!

Book Synopsis Deep Learning and Data Labeling for Medical Applications by : Gustavo Carneiro

Download or read book Deep Learning and Data Labeling for Medical Applications written by Gustavo Carneiro and published by Springer. This book was released on 2016-10-07 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods; active learning; transfer learning; semi-supervised learning; and modeling of label uncertainty.The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques.

Early Prediction of Diseases using Deep Learning and Machine Learning Techniques

Author : Dr. Sasidhar B
Publisher : Archers & Elevators Publishing House
ISBN 13 : 8119385497
Total Pages : 85 pages
Book Rating : 4.1/5 (193 download)

DOWNLOAD NOW!

Book Synopsis Early Prediction of Diseases using Deep Learning and Machine Learning Techniques by : Dr. Sasidhar B

Download or read book Early Prediction of Diseases using Deep Learning and Machine Learning Techniques written by Dr. Sasidhar B and published by Archers & Elevators Publishing House. This book was released on with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Brain Tumor Classification Using Convolutional Neural Network with Neutrosophy, Super-Resolution and SVM

Author : Mubashir Tariq
Publisher : Infinite Study
ISBN 13 :
Total Pages : 24 pages
Book Rating : 4./5 ( download)

DOWNLOAD NOW!

Book Synopsis Brain Tumor Classification Using Convolutional Neural Network with Neutrosophy, Super-Resolution and SVM by : Mubashir Tariq

Download or read book Brain Tumor Classification Using Convolutional Neural Network with Neutrosophy, Super-Resolution and SVM written by Mubashir Tariq and published by Infinite Study. This book was released on 2022-01-01 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the domain of Medical Image Analysis (MIA), it is difficult to perform brain tumor classification. With the help of machine learning technology and algorithms, brain tumor can be easily diagnosed by the radiologists without practicing any surgical approach. In the previous few years, remarkable progress has been observed by deep learning techniques in the domain of MIA. Although, the classification of brain tumor through Magnetic Resonance Imaging (MRI) has seen multiple problems: 1) the structure of brain and complexity of brain tissues; 2) deriving the classification of brain tumor due to brain’s nature of high-density. To study the classification of brain tumor; inculcating the normal and abnormal MRI, this study has designed a blended method by using Neutrosophic Super Resolution (NSR) with Fuzzy-C-Means (FCM) and Convolutional Neural Network (CNN).Initially, non-local mean filtered MRI provided Neutrosophic Super Resolution (NSR) image, however, for enhancement of clustering and simulation of the brain tumor along with the reduction of time consumption, efficiency and accuracy without any technical hindrance Support vector Machine (SVM) guided FCM was applied. Consequently, the recommended method resulted in an excellent performance with 98.12%, 98.2% of average success about sensitivity and 1.8% of error rate brain tumor image.

Machine Learning and Deep Learning Techniques for Medical Image Recognition

Author : Ben Othman Soufiene
Publisher : CRC Press
ISBN 13 : 1003805671
Total Pages : 270 pages
Book Rating : 4.0/5 (38 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning and Deep Learning Techniques for Medical Image Recognition by : Ben Othman Soufiene

Download or read book Machine Learning and Deep Learning Techniques for Medical Image Recognition written by Ben Othman Soufiene and published by CRC Press. This book was released on 2023-12-01 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Multimodal Brain Tumor Segmentation and Beyond

Author : Bjoern Menze
Publisher : Frontiers Media SA
ISBN 13 : 2889711706
Total Pages : 324 pages
Book Rating : 4.8/5 (897 download)

DOWNLOAD NOW!

Book Synopsis Multimodal Brain Tumor Segmentation and Beyond by : Bjoern Menze

Download or read book Multimodal Brain Tumor Segmentation and Beyond written by Bjoern Menze and published by Frontiers Media SA. This book was released on 2021-08-10 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Imaging of Brain Tumors with Histological Correlations

Author : Antonios Drevelegas
Publisher : Springer Science & Business Media
ISBN 13 : 3662049511
Total Pages : 306 pages
Book Rating : 4.6/5 (62 download)

DOWNLOAD NOW!

Book Synopsis Imaging of Brain Tumors with Histological Correlations by : Antonios Drevelegas

Download or read book Imaging of Brain Tumors with Histological Correlations written by Antonios Drevelegas and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides a thorough treatment of the diagnosis of brain tumors by correlating radiographic image features to the underlying pathology. Theoretical considerations and illustrations depicting common and uncommon imaging characteristics of various brain tumors are presented. All modern imaging modalities are used to complete a diagnostic overview of brain tumors with emphasis on recent advances in diagnostic neuroradiology. The book has been designed as a clinical tool for radiologists and other clinicians interested in the current diagnostic approach to brain tumors.

Smart Computing Techniques and Applications

Author : Suresh Chandra Satapathy
Publisher : Springer Nature
ISBN 13 : 9811615020
Total Pages : 801 pages
Book Rating : 4.8/5 (116 download)

DOWNLOAD NOW!

Book Synopsis Smart Computing Techniques and Applications by : Suresh Chandra Satapathy

Download or read book Smart Computing Techniques and Applications written by Suresh Chandra Satapathy and published by Springer Nature. This book was released on 2021-07-13 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents best selected papers presented at the 4th International Conference on Smart Computing and Informatics (SCI 2020), held at the Department of Computer Science and Engineering, Vasavi College of Engineering (Autonomous), Hyderabad, Telangana, India. It presents advanced and multi-disciplinary research towards the design of smart computing and informatics. The theme is on a broader front which focuses on various innovation paradigms in system knowledge, intelligence and sustainability that may be applied to provide realistic solutions to varied problems in society, environment and industries. The scope is also extended towards the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology and health care.

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015

Author : Nassir Navab
Publisher : Springer
ISBN 13 : 3319245740
Total Pages : 801 pages
Book Rating : 4.3/5 (192 download)

DOWNLOAD NOW!

Book Synopsis Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 by : Nassir Navab

Download or read book Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015 written by Nassir Navab and published by Springer. This book was released on 2015-09-28 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 9349, 9350, and 9351 constitutes the refereed proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015, held in Munich, Germany, in October 2015. Based on rigorous peer reviews, the program committee carefully selected 263 revised papers from 810 submissions for presentation in three volumes. The papers have been organized in the following topical sections: quantitative image analysis I: segmentation and measurement; computer-aided diagnosis: machine learning; computer-aided diagnosis: automation; quantitative image analysis II: classification, detection, features, and morphology; advanced MRI: diffusion, fMRI, DCE; quantitative image analysis III: motion, deformation, development and degeneration; quantitative image analysis IV: microscopy, fluorescence and histological imagery; registration: method and advanced applications; reconstruction, image formation, advanced acquisition - computational imaging; modelling and simulation for diagnosis and interventional planning; computer-assisted and image-guided interventions.

Brain Tumor Segmentation Using Deep Learning Technique

Author : Oyesh Mann Singh
Publisher :
ISBN 13 :
Total Pages : 108 pages
Book Rating : 4.:/5 (1 download)

DOWNLOAD NOW!

Book Synopsis Brain Tumor Segmentation Using Deep Learning Technique by : Oyesh Mann Singh

Download or read book Brain Tumor Segmentation Using Deep Learning Technique written by Oyesh Mann Singh and published by . This book was released on 2017 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Deep Learning for Medical Image Analysis

Author : S. Kevin Zhou
Publisher : Academic Press
ISBN 13 : 0323858880
Total Pages : 544 pages
Book Rating : 4.3/5 (238 download)

DOWNLOAD NOW!

Book Synopsis Deep Learning for Medical Image Analysis by : S. Kevin Zhou

Download or read book Deep Learning for Medical Image Analysis written by S. Kevin Zhou and published by Academic Press. This book was released on 2023-12-01 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for academic and industry researchers and graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. Deep learning provides exciting solutions for medical image analysis problems and is a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component are applied to medical image detection, segmentation, registration, and computer-aided analysis. · Covers common research problems in medical image analysis and their challenges · Describes the latest deep learning methods and the theories behind approaches for medical image analysis · Teaches how algorithms are applied to a broad range of application areas including cardiac, neural and functional, colonoscopy, OCTA applications and model assessment · Includes a Foreword written by Nicholas Ayache

Deep Learning in Biomedical Signal and Medical Imaging

Author : Ngangbam Herojit Singh
Publisher : CRC Press
ISBN 13 : 1040107117
Total Pages : 274 pages
Book Rating : 4.0/5 (41 download)

DOWNLOAD NOW!

Book Synopsis Deep Learning in Biomedical Signal and Medical Imaging by : Ngangbam Herojit Singh

Download or read book Deep Learning in Biomedical Signal and Medical Imaging written by Ngangbam Herojit Singh and published by CRC Press. This book was released on 2024-09-30 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Approaches and Applications of Deep Learning in Virtual Medical Care

Author : Zaman, Noor
Publisher : IGI Global
ISBN 13 : 1799889300
Total Pages : 293 pages
Book Rating : 4.7/5 (998 download)

DOWNLOAD NOW!

Book Synopsis Approaches and Applications of Deep Learning in Virtual Medical Care by : Zaman, Noor

Download or read book Approaches and Applications of Deep Learning in Virtual Medical Care written by Zaman, Noor and published by IGI Global. This book was released on 2022-02-25 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: The recent advancements in the machine learning paradigm have various applications, specifically in the field of medical data analysis. Research has proven the high accuracy of deep learning algorithms, and they have become a standard choice for analyzing medical data, especially medical images, video, and electronic health records. Deep learning methods applied to electronic health records are contributing to understanding the evolution of chronic diseases and predicting the risk of developing those diseases. Approaches and Applications of Deep Learning in Virtual Medical Care considers the applications of deep learning in virtual medical care and delves into complex deep learning algorithms, calibrates models, and improves the predictions of the trained model on medical imaging. Covering topics such as big data and medical sensors, this critical reference source is ideal for researchers, academicians, practitioners, industry professionals, hospital workers, scholars, instructors, and students.

Intramedullary Spinal Cord Tumors

Author : Georges Fischer
Publisher : Thieme
ISBN 13 : 9780865775930
Total Pages : 132 pages
Book Rating : 4.7/5 (759 download)

DOWNLOAD NOW!

Book Synopsis Intramedullary Spinal Cord Tumors by : Georges Fischer

Download or read book Intramedullary Spinal Cord Tumors written by Georges Fischer and published by Thieme. This book was released on 1996 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is the first book in 30 years to cover all diagnostic and therapeutic aspects of intramedullary spinal cord tumors (IMTs), a relatively rare but often misdiagnosed type of tumor. You will benefit from the largest personal collection of operated cases (171) ever assembled, as well as a review of 1,100 additional cases, making this the single most comprehensive book on IMTs available today. You will also appreciate the vital role of MRI in accurately diagnosing these tumors and review the latest technical refinements in surgical methods. Divided into three parts, the book begins with the diagnostic and therapeutic problems common to all intramedullary spinal cord tumors, then covers the histology of individual tumors, and finally examines the controversial value of radiotherapy in the treatment of both benign and malignant tumors in children and adults. Throughout, full-color illustrations depict anatomy from a surgical point of view.