Computational Intelligence in Medical Imaging: Techniques and Applications

G. Schaefer, A. Hassanien, J. Jiang

September 12, 2017 by Chapman and Hall/CRC
Reference - 510 Pages - 23 Color & 248 B/W Illustrations
ISBN 9781138112209 - CAT# K35150

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Features

  • Presents the current state of the art in various areas of computational intelligence
  • Reflects forefront research in intelligent medical image processing
  • Explores a range of computational algorithms and techniques, such as neural networks, fuzzy sets, and evolutionary optimization
  • Encompasses many important applications, including the identification of melanoma and prostate cancer analysis
  • Describes a comprehensive system for handling and using biomedical image databases

Summary

CI Techniques & Algorithms for a Variety of Medical Imaging Situations
Documents recent advances and stimulates further research

A compilation of the latest trends in the field, Computational Intelligence in Medical Imaging: Techniques and Applications explores how intelligent computing can bring enormous benefit to existing technology in medical image processing as well as improve medical imaging research. The contributors also cover state-of-the-art research toward integrating medical image processing with artificial intelligence and machine learning approaches.

The book presents numerous techniques, algorithms, and models. It describes neural networks, evolutionary optimization techniques, rough sets, support vector machines, tabu search, fuzzy logic, a Bayesian probabilistic framework, a statistical parts-based appearance model, a reinforcement learning-based multistage image segmentation algorithm, a machine learning approach, Monte Carlo simulations, and intelligent, deformable models. The contributors discuss how these techniques are used to classify wound images, extract the boundaries of skin lesions, analyze prostate cancer, handle the inherent uncertainties in mammographic images, and encapsulate the natural intersubject anatomical variance in medical images. They also examine prostate segmentation in transrectal ultrasound images, automatic segmentation and diagnosis of bone scintigraphy, 3-D medical image segmentation, and the reconstruction of SPECT and PET tomographic images.

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