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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