Image Processing and Acquisition using Python

Introduction to Images and Computing using Python
Introduction to Python
Introduction
What Is Python?
Python Environments
Running a Python Program
Basic Python Statements and Data Types





Computing using Python Modules
Introduction
Python Modules
Numpy
Scipy
Matplotlib
Python Imaging Library
Scikits
Python OpenCV Module





Image and Its Properties
Introduction
Image and Its Properties
Image Types
Data Structures for Image Analysis
Programming Paradigm





Image Processing using Python
Spatial Filters
Introduction
Filtering
Edge Detection using Derivatives





Image Enhancement
Introduction
Pixel Transformation
Image Inverse
Power Law Transformation
Log Transformation
Histogram Equalization
Contrast Stretching





Fourier Transform
Introduction
Definition of Fourier Transform
Two-Dimensional Fourier Transform
Convolution
Filtering in Frequency Domain





Segmentation
Introduction
Histogram-Based Segmentation
Region-Based Segmentation
Segmentation Algorithm for Various Modalities





Morphological Operations
Introduction
History
Dilation
Erosion
Grayscale Dilation and Erosion
Opening and Closing
Hit-or-Miss
Thickening and Thinning





Image Measurements
Introduction
Labeling
Hough Transform
Template Matching





Image Acquisition
X-Ray and Computed Tomography
Introduction
History
X-Ray Generation
Material Properties
X-Ray Detection
X-Ray Imaging Modes
Computed Tomography (CT)
Hounsfield Unit (HU)
Artifacts





Magnetic Resonance Imaging
Introduction
Laws Governing NMR and MRI
Material Properties
NMR Signal Detection
MRI Signal Detection or MRI Imaging
MRI Construction
T1, T2, and Proton Density Image
MRI Modes or Pulse Sequence
MRI Artifacts





Light Microscopes
Introduction
Physical Principles
Construction of a Wide-Field Microscope
Epi-Illumination
Fluorescence Microscope
Confocal Microscopes
Nipkow Disk Microscopes
Confocal or Wide-Field?





Electron Microscopes
Introduction
Physical Principles
Construction of EM
Specimen Preparations
Construction of TEM
Construction of SEM



Appendix A: Installing Python Distributions
Appendix B: Parallel Programming Using MPI4Py
Appendix C: Introduction to ImageJ
Appendix D: MATLAB and Numpy Functions





Index





A Summary and Exercises appear at the end of each chapter.