rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Handbook of Texture Analysis
    sub title: AI-Based medical imaging Applications
    part number: Volume II
  name:
    name part: El-Baz, Ayman S.
    role:
      role term: editor.
  name:
    name part: Ghazal, Mohammad
    role:
      role term: editor.
  name:
    name part: Suri, Jasjit S.
    role:
      role term: editor.
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    date issued: 2024
    edition: First edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xxii, 248 pages).
  abstract: 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.
  table of contents: 1 An Exploratory Review on Local Binary Descriptors for Texture Classification 2 Precision Grading of Glioma: A System for Accurate Diagnosis and Treatment Planning 3 Enhancing Accuracy in Liver Tumor Detection and Grading: A Computer-Aided Diagnostic System 4 Texture Analysis in Radiology 5 Texture Analysis Using a Self-Organizing Feature Map 6 Sensor-Based Human Activity Recognition Analysis Using Machine Learning and Topological Data Analysis (TDA) 7 Application of Texture Analysis in Retinal OCT Imaging 8 Automation in Pneumonia Detection 9 Texture for Neuroimaging 10 A Multimodal MR-Based CAD System for Precise Assessment of Prostatic Adenocarcinoma 11 Texture Analysis in Cancer Prognosis
  target audience: general
  note: edited by Ayman El-Baz, Mohammad Ghazal, Jasjit S. Suri.
  note: Ayman El-Baz is a Distinguished Professor at University of Louisville, Kentucky, United States and University of Louisville at Alamein International University (UofL-AIU), New Alamein City, Egypt. Dr. El-Baz earned his B.Sc. and M.Sc. degrees in electrical engineering in 1997 and 2001, respectively. He earned his Ph.D. in electrical engineering from the University of Louisville in 2006. Dr. El-Baz was named as a Fellow for IEEE, Coulter, AIMBE and NAI for his contributions to the field of biomedical translational research. Dr. El-Baz has almost two decades of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnosis systems. He has authored or coauthored more than 700 technical articles. Mohammed Ghazal is a Professor and Chairman of the Department of Electrical, Computer, and Biomedical Engineering at the College of Engineering, Abu Dhabi University, UAE. His research areas are bioengineering, image and video processing, and smart systems. He received his Ph.D and M.A.Sc in Electrical and Computer Engineering (ECE) from Concordia University in Montreal Canada in 2010 and 2006, respectively, and his B.Sc. in Computer Engineering from the American University of Sharjah (AUS) in 2004. He has received multiple awards including the Distinguished Faculty Award of Abu Dhabi University in 2017 and 2014. Dr. Ghazal has authored or co-authored over 70 publications in recognized international journals and conferences including IEEE Transactions in Image Processing, IEEE Transactions in Circuits and Systems for Video Technology, IEEE Transactions in Consumer Electronics, Elsevier's Renewable Energy Reviews, and Springer's Multimedia Tools and Applications. Jasjit S. Suri is an innovator, scientist, visionary, industrialist and an internationally known world leader in biomedical engineering. Dr. Suri has spent over 25 years in the field of biomedical engineering/devices and its management. He received his Ph.D. from the University of…
  subject:
    topic: Computer vision
  subject:
    topic: Texture (Art)
  subject:
    topic: Vision par ordinateur
  subject:
    topic: Texture (Art)
  subject:
    topic: texture (artistic concept)
  subject:
    topic: COMPUTERS / Computer Graphics / Image Processing (see also PHOTOGRAPHY / Techniques / Digital)
  classification: TA1634
  classification: 006.3/7
  identifier: 9780367486082
  identifier: 0367486083
  identifier: 9780367483456
  identifier: 9781040008973
  identifier: 1040008976
  identifier: 9781032727431
  identifier: 9781040008904
  identifier: 1040008909
  identifier: 9780367486082 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: TYFRS
    record creation date: 240627
    record change date: 20241108170140.9
    record identifier: in00005524021
    language of cataloging:
      language term: eng