Image Processing with MATLAB

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A01=Musa H. Asyali
A01=Omer Demirkaya
A01=Prasanna K. Sahoo
Author_Musa H. Asyali
Author_Omer Demirkaya
Author_Prasanna K. Sahoo
biomedical signal processing
Category=UF
Category=UYT
CT Image
CT Scanner
Cumulative Distribution Function
deformable
Deformable Models
deformable shape models
detection
DFT Coefficient
DFT Magnitude
discrete
edge
Em Algorithm
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
fast Fourier analysis
fourier
fuzzy clustering algorithms
Gamma Camera System
gaussian
Generalized Beta Distribution
Geometric Deformable Models
Gibbs Sampler
graduate level imaging
Gray Level Histogram
Gray Level Image
Hough Transform
ICM
ICM Algorithm
Image Processing Toolbox
kernel
LSF
magnitude
MATLAB Image Processing Toolbox
MATLAB Script
Metropolis Algorithm
models
nonlinear diffusion segmentation methods
Optimal Threshold
Parametric Deformable Models
Pet Image
probabilistic modelling
Probability Density Function
transform

Product details

  • ISBN 9780849392467
  • Weight: 860g
  • Dimensions: 156 x 234mm
  • Publication Date: 22 Dec 2008
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Image Processing with MATLAB®: Applications in Medicine and Biology explains complex, theory-laden topics in image processing through examples and MATLAB® algorithms. It describes classical as well emerging areas in image processing and analysis.

Providing many unique MATLAB codes and functions throughout, the book covers the theory of probability and statistics, two-dimensional fast Fourier transform, nonlinear diffusion filtering, and partial differential equation (PDE)-based image denoising techniques. It presents intensity-based image segmentation methods, including thresholding techniques as well as K-means and fuzzy C-means clustering techniques. The authors also explore Markov random field (MRF)-based image segmentation, boundary and curvature analysis methods, and parametric and geometric deformable models. The final chapters focus on three specific applications of image processing and analysis.

Reducing the need for the trial-and-error way of solving problems, this book helps readers understand advanced concepts by applying algorithms to real-world problems in medicine and biology.

A solutions manual is available for instructoes wishing to convert this reference to classroom use.

Omer Demirkaya, Musa H. Asyali, Prasanna K. Sahoo

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