Ayman El-Baz – författare
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61 produkter
61 produkter
5 552 kr
Skickas inom 10-15 vardagar
This two-volume handbook provides a comprehensive view of texture analysis in both AI-based industrial and medical imaging applications. The first volume covers texture analysis for neuroradiology; information-theoretic entropy; chronic liver diseases; clinical management of focal liver lesions; abdominal imaging; optical coherence tomography images; thoracic imaging; prostate cancer; breast cancer; bladder cancer, quality evaluation of meat products; and detection of powdery mildew on strawberry leaves. The second volume covers Local Binary Descriptors for Texture Classification; Precision Grading of Glioma; Liver Tumor Detection and Grading; Texture Analysis in Radiology; Texture Analysis Using a Self-Organizing Feature Map; Sensor-Based Human Activity Recognition Analysis Using Machine Learning and Topological Data Analysis; Texture Analysis in Retinal OCT Imaging; Pneumonia Detection; Prostatic Adenocarcinoma; and Texture Analysis in Cancer Prognosis. Aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineering, this handbook is an essential reference for those looking to advance their understanding in this applied and emergent field.
Inbunden, Engelska, 2024
2 358 kr
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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 filtersExamines textural features for image classification, a statistical approach for classification, texture classification from random features, and applications of texture classificationsDescribes shape from texture, including general principles, 3D shapes, and equations for recovering shape from textureSurveys texture modeling, including extraction based on Hough transformation and cycle detection, image quilting, gray level run lengths, and use of Markov random fieldsAimed 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.
Inbunden, Engelska, 2024
2 358 kr
Skickas inom 10-15 vardagar
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 methodsCovers spatial frequency-based methods, Fourier analysis, Markov random fields, Gabor filters, and Hough transformationDescribes advanced textural methods based on DL as well as BD and advanced applications of texture to medial image segmentationIs aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineeringThis is an essential reference for those looking to advance their understanding in this applied and emergent field.
Inbunden, Engelska, 2023
2 215 kr
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Today’s healthcare organizations must focus on a lot more than just the health of their clients. The infrastructure it takes to support clinical-care delivery continues to expand, with information technology being one of the most significant contributors to that growth. As companies have become more dependent on technology for their clinical, administrative, and financial functions, their IT departments and expenditures have had to scale quickly to keep up. However, as technology demands have increased, so have the options for reliable infrastructure for IT applications and data storage. The one that has taken center stage over the past few years is cloud computing. Healthcare researchers are moving their efforts to the cloud because they need adequate resources to process, store, exchange, and use large quantities of medical data.Cloud Computing in Medical Imaging covers the state-of-the-art techniques for cloud computing in medical imaging, healthcare technologies, and services. The book focuses on Machine-learning algorithms for health data security Fog computing in IoT-based health care Medical imaging and healthcare applications using fog IoT networks Diagnostic imaging and associated services Image steganography for medical informaticsThis book aims to help advance scientific research within the broad field of cloud computing in medical imaging, healthcare technologies, and services. It focuses on major trends and challenges in this area and presents work aimed to identify new techniques and their use in biomedical analysis.
Häftad, Engelska, 2019
1 788 kr
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As one of the most important tasks in biomedical imaging, image segmentation provides the foundation for quantitative reasoning and diagnostic techniques. A large variety of different imaging techniques, each with its own physical principle and characteristics (e.g., noise modeling), often requires modality-specific algorithmic treatment. In recent years, substantial progress has been made to biomedical image segmentation. Biomedical image segmentation is characterized by several specific factors. This book presents an overview of the advanced segmentation algorithms and their applications.
Häftad, Engelska, 2019
1 104 kr
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This book covers state-of-the-art medical image analysis approaches currently pursued in autism research. Chapters cover recent advances in diagnosis using structural neuroimaging. All aspects of imaging are included, such as electrophysiology (EEG, ERP, QEEG, and MEG), postmortem techniques, and advantages and difficulties of depositing/acquiring images in larger databases. The book incorporates 2D, 3D, and 4D imaging and advances scientific research within the broad field of autism imaging.
Inbunden, Engelska, 2019
1 902 kr
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Inbunden, Engelska, 2019
1 902 kr
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Häftad, Engelska, 2019
408 kr
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Inbunden, Engelska, 2019
1 902 kr
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Häftad, Engelska, 2019
408 kr
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Inbunden, Engelska, 2020
1 919 kr
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Häftad, Engelska, 2020
408 kr
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Häftad, Engelska, 2019
408 kr
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Inbunden, Engelska, 2023
2 586 kr
Skickas inom 3-6 vardagar
Häftad, Engelska, 2023
478 kr
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Inbunden, Engelska, 2022
2 586 kr
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Häftad, Engelska, 2022
478 kr
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Inbunden, Engelska, 2021
1 902 kr
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Häftad, Engelska, 2021
408 kr
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Inbunden, Engelska, 2019
1 902 kr
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Häftad, Engelska, 2019
408 kr
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Inbunden, Engelska, 2020
1 919 kr
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Häftad, Engelska, 2020
408 kr
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Inbunden, Engelska, 2022
1 902 kr
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Häftad, Engelska, 2022
408 kr
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Inbunden, Engelska, 2026
1 902 kr
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Häftad, Engelska, 2026
408 kr
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Inbunden, Engelska, 2022
1 847 kr
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Häftad, Engelska, 2022
408 kr
Skickas inom 5-8 vardagar