Download or read book Texture Analysis for Magnetic Resonance Imaging written by Milan Hájek and published by Texture Analysis Magn Resona. This book was released on 2006 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Use of Texture Analysis in Breast Magnetic Resonance Imaging written by Shelley Ann Waugh and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Application of Texture Analysis to Dynamic Contrast Enhanced Breast Magnetic Resonance Imaging written by Sachin Jambawalikar and published by . This book was released on 2005 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Advances in Distributed Computing and Machine Learning written by Jyoti Prakash Sahoo and published by Springer Nature. This book was released on 2022-01-01 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances in the field of scalable distributed computing including state-of-the-art research in the field of Cloud Computing, the Internet of Things (IoT), and Blockchain in distributed environments along with applications and findings in broad areas including Data Analytics, AI, and Machine Learning to address complex real-world problems. It features selected high-quality research papers from the 2nd International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2021), organized by the Department of Computer Science and Information Technology, Institute of Technical Education and Research(ITER), Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India.

Download or read book Handbook of Texture Analysis written by Ayman El-Baz and published by CRC Press. This book was released on 2024-06-21 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: The major goals of texture research in computer vision are to understand, model, and process texture and, ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This book: Discusses first-order, second-order statistical methods, local binary pattern (LBP) methods, and filter bank-based methods Covers spatial frequency-based methods, Fourier analysis, Markov random fields, Gabor filters, and Hough transformation Describes advanced textural methods based on DL as well as BD and advanced applications of texture to medial image segmentation Is aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineering This is an essential reference for those looking to advance their understanding in this applied and emergent field.

Download or read book The Application of Texture Analysis for the Study of Liver Disease by Magnetic Resonance Imaging written by Akbar Gharbali and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Haralick Texture Analysis of Simulated Microcalcification Effects in Breast Magnetic Resonance Imaging written by David Conrad James and published by . This book was released on 2000 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Handbook of Texture Analysis written by Ayman El-Baz and published by CRC Press. This book was released on 2024-06-24 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: The major goals of texture research in computer vision are to understand, model, and process texture, and ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This book examines four major application domains related to texture analysis and their relationship to AI-based industrial applications: texture classification, texture segmentation, shape from texture, and texture synthesis. This volume: Discusses texture-based segmentation for extracting image shape features, modeling and segmentation of noisy and textured images, spatially constrained color-texture model for image segmentation, and texture segmentation using Gabor filters Examines textural features for image classification, a statistical approach for classification, texture classification from random features, and applications of texture classifications Describes shape from texture, including general principles, 3D shapes, and equations for recovering shape from texture Surveys texture modeling, including extraction based on Hough transformation and cycle detection, image quilting, gray level run lengths, and use of Markov random fields Aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineering, this is an essential reference for those looking to advance their understanding in this applied and emergent field.

Download or read book Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning written by Rani, Geeta and published by IGI Global. This book was released on 2020-10-16 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

Download or read book Biomedical Texture Analysis written by Adrien Depeursinge and published by Academic Press. This book was released on 2017-08-25 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biomedical Texture Analysis: Fundamentals, Applications, Tools and Challenges describes the fundamentals and applications of biomedical texture analysis (BTA) for precision medicine. It defines what biomedical textures (BTs) are and why they require specific image analysis design approaches when compared to more classical computer vision applications. The fundamental properties of BTs are given to highlight key aspects of texture operator design, providing a foundation for biomedical engineers to build the next generation of biomedical texture operators. Examples of novel texture operators are described and their ability to characterize BTs are demonstrated in a variety of applications in radiology and digital histopathology. Recent open-source software frameworks which enable the extraction, exploration and analysis of 2D and 3D texture-based imaging biomarkers are also presented. This book provides a thorough background on texture analysis for graduate students and biomedical engineers from both industry and academia who have basic image processing knowledge. Medical doctors and biologists with no background in image processing will also find available methods and software tools for analyzing textures in medical images. - Defines biomedical texture precisely and describe how it is different from general texture information considered in computer vision - Defines the general problem to translate 2D and 3D texture patterns from biomedical images to visually and biologically relevant measurements - Describes, using intuitive concepts, how the most popular biomedical texture analysis approaches (e.g., gray-level matrices, fractals, wavelets, deep convolutional neural networks) work, what they have in common, and how they are different - Identifies the strengths, weaknesses, and current challenges of existing methods including both handcrafted and learned representations, as well as deep learning. The goal is to establish foundations for building the next generation of biomedical texture operators - Showcases applications where biomedical texture analysis has succeeded and failed - Provides details on existing, freely available texture analysis software, helping experts in medicine or biology develop and test precise research hypothesis

Download or read book Image Processing and Capsule Networks written by Joy Iong-Zong Chen and published by Springer Nature. This book was released on 2020-07-23 with total page 829 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book emphasizes the emerging building block of image processing domain, which is known as capsule networks for performing deep image recognition and processing for next-generation imaging science. Recent years have witnessed the continuous development of technologies and methodologies related to image processing, analysis and 3D modeling which have been implemented in the field of computer and image vision. The significant development of these technologies has led to an efficient solution called capsule networks [CapsNet] to solve the intricate challenges in recognizing complex image poses, visual tasks, and object deformation. Moreover, the breakneck growth of computation complexities and computing efficiency has initiated the significant developments of the effective and sophisticated capsule network algorithms and artificial intelligence [AI] tools into existence. The main contribution of this book is to explain and summarize the significant state-of-the-art research advances in the areas of capsule network [CapsNet] algorithms and architectures with real-time implications in the areas of image detection, remote sensing, biomedical image analysis, computer communications, machine vision, Internet of things, and data analytics techniques.

Download or read book Magnetic Resonance in Food Science written by Peter S Belton and published by Royal Society of Chemistry. This book was released on 2007-10-31 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: The term magnetic resonance covers a wide range of techniques, spectroscopy, relaxation and imaging. In turn, these areas are evolving and leading to various new applications of NMR and ESR in food science and nutrition. From assessment of meat quality, through to a study of beer components and the effect of microwaves on potato texture, Magnetic Resonance in Food Science: Latest Developments provides an account of the state of the art in this lively area. Coverage includes: recent developments in magnetic resonance; human aspects of food; structure and dynamics in food; and food quality control. With contributions from international experts, this book is essential reading for academics and industrialists in food science. It is the latest in a series of titles in this area published by the RSC.

Download or read book Imaging of Brain Tumors An Issue of Magnetic Resonance Imaging Clinics of North America written by Rivka R. Colen and published by Elsevier Health Sciences. This book was released on 2016-10-15 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This issue of MRI Clinics of North America focuses on Imaging of Brain Tumors, and is edited by Dr. Rivka Colen. Articles will include: Multiparametric Imaging Analysis: MR Spectroscopy; Genomics and MicroRNAs in Glioma; Metabolomics and Hyperpolarization MRI in Brain Tumors; Imaging Genomics in Glioma; Radiomics and Big Data in Imaging; RANO Criteria and Clinical Endpoints; Gliomas: The New WHO Brain Tumor Pathological/Molecular Classification and Clinical and Radiographic Classifications; Liposomal Contrast Agents and Nanoparticles in Brain Tumor Imaging; Multiparametric Imaging Analysis: Perfusion, and more!

Download or read book Computer Information Systems and Industrial Management written by Khalid Saeed and published by Springer. This book was released on 2015-09-17 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 14th IFIP TC 8 International Conference on Computer Information Systems and Industrial Management, CISIM 2015, held in Warsaw, Poland, in September 2015. The 47 papers presented in this volume were carefully reviewed and selected from about 80 submissions. The main topics covered are biometrics, security systems, multimedia, classification and clustering with applications, and industrial management.

Download or read book Breakthrough in Imaging Guided Precision Medicine in Oncology written by Laurent Dercle and published by Frontiers Media SA. This book was released on 2022-03-11 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Image Texture Analysis written by Chih-Cheng Hung and published by Springer. This book was released on 2019-06-05 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis. Topics and features: provides self-test exercises in every chapter; describes the basics of image texture, texture features, and image texture classification and segmentation; examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification; explains the concepts of dimensionality reduction and sparse representation; discusses view-based approaches to classifying images; introduces the template for the K-views algorithm, as well as a range of variants of this algorithm; reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks. This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work.

Download or read book Search Texture Analysis of Multimodal Magnetic Resonance Images in Support of Diagnostic Classification of Childhood Brain Tumours written by Suchada Tantisatirapong and published by . This book was released on 2014 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: