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Surface Imaging for Biomedical Applications (Paperback)
Loot Price: R2,413
Discovery Miles 24 130
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Surface Imaging for Biomedical Applications (Paperback)
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Total price: R2,433
Discovery Miles: 24 330
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Based on hospital clinical trials examining the use of signal and
image processing techniques, Surface Imaging for Biomedical
Applications bridges the gap between engineers and clinicians. This
text offers a thorough analysis of biomedical surface imaging to
medical practitioners as it relates to the diagnosis, detection,
and monitoring of skin conditions and disease. Written from an
engineer's perspective, the book discusses image acquisition
methods, image processing, and pattern recognition techniques. It
focuses on a variety of techniques used in recent years for image
processing and pattern recognition (principal component analysis,
independent component analysis, singular value decomposition,
texture modeling, inverse model analysis, polynomial surface
fitting, and classification techniques), and considers
interventional and non-invasive procedures used to diagnose
skin-related disease. It examines the biological causation of four
skin disorders (psoriasis, vitiligo, ulcer, and acne), provides
basic terminologies in surface imaging, and details the outcome of
various clinical observations and other research. It also details
numerous measurement parameters related to surface imaging (body
surface, skin color, tissue characteristic, thickness, roughness,
volume of skin, and retinal changes). Discusses the development of
a psoriasis severity measurement tool Provides material on
assessing segmented repigmentation areas in vitiligo patients via
VT-Scan Introduces a volume ulcer assessment using non-invasive 3D
imaging Presents an automated system for acne grading that is based
on capturing the images of various body parts using the DSLR camera
Includes the MATLAB (R) codes for various pattern recognition
techniques applied during the assessment/measurement at the end of
each chapter This interdisciplinary reference highlights the
importance of disease diagnosis and monitoring, and is suitable for
medical practitioners, biomedical engineers, and core image
processing researchers.
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