Contents

Foreword

Preface

Preface to the First Edition

Introduction

Authors

List of Symbols and Abbreviations

IIntroduction to Images and Computing using Python

1Introduction to Python

1.1Introduction

1.2What Is Python?

1.3Python Environments

1.3.1Python Interpreter

1.3.2Anaconda Python Distribution

1.4Running a Python Program

1.5Basic Python Statements and Data Types

1.5.1Data Structures

1.5.2File Handling

1.5.3User-Defined Functions

1.6Summary

1.7Exercises

2Computing using Python Modules

2.1Introduction

2.2Python Modules

2.2.1Creating Modules

2.2.2Loading Modules

2.3Numpy

2.3.1Numpy Array or Matrices?

2.4Scipy

2.5Matplotlib

2.6Python Imaging Library

2.7Scikits

2.8Python OpenCV Module

2.9Summary

2.10Exercises

3Image and Its Properties

3.1Introduction

3.2Image and Its Properties

3.2.1Bit-Depth

3.2.2Pixel and Voxel

3.2.3Image Histogram

3.2.4Window and Level

3.2.5Connectivity: 4 or 8 Pixels

3.3Image Types

3.3.1JPEG

3.3.2TIFF

3.3.3DICOM

3.4Data Structures for Image Analysis

3.5Reading, Writing and Displaying Images

3.5.1Reading Images

3.5.2Reading DICOM Images using pyDICOM

3.5.3Writing Images

3.5.4Writing DICOM Images using pyDICOM

3.5.5Displaying Images

3.6Programming Paradigm

3.7Summary

3.8Exercises

IIImage Processing using Python

4Spatial Filters

4.1Introduction

4.2Filtering

4.2.1Mean Filter

4.2.2Median Filter

4.2.3Max Filter

4.2.4Min Filter

4.3Edge Detection using Derivatives

4.3.1First Derivative Filters

4.3.1.1Sobel Filter

4.3.1.2Prewitt Filter

4.3.1.3Canny Filter

4.3.2Second Derivative Filters

4.3.2.1Laplacian Filter

4.3.2.2Laplacian of Gaussian Filter

4.4Shape Detecting Filter

4.4.1Frangi Filter

4.5Summary

4.6Exercises

5Image Enhancement

5.1Introduction

5.2Pixel Transformation

5.3Image Inverse

5.4Power Law Transformation

5.5Log Transformation

5.6Histogram Equalization

5.7Contrast Limited Adaptive Histogram Equalization (CLAHE)

5.8Contrast Stretching

5.9Sigmoid Correction

5.10Local Contrast Normalization

5.11Summary

5.12Exercises

6Affine Transformation

6.1Introduction

6.2Affine Transformation

6.2.1Translation

6.2.2Rotation

6.2.3Scaling

6.2.4Interpolation

6.3Summary

6.4Exercises

7Fourier Transform

7.1Introduction

7.2Definition of Fourier Transform

7.3Two-Dimensional Fourier Transform

7.3.1Fast Fourier Transform using Python

7.4Convolution

7.4.1Convolution in Fourier Space

7.5Filtering in the Frequency Domain

7.5.1Ideal Lowpass Filter

7.5.2Butterworth Lowpass Filter

7.5.3Gaussian Lowpass Filter

7.5.4Ideal Highpass Filter

7.5.5Butterworth Highpass Filter

7.5.6Gaussian Highpass Filter

7.5.7Bandpass Filter

7.6Summary

7.7Exercises

8Segmentation

8.1Introduction

8.2Histogram-Based Segmentation

8.2.1Otsu’s Method

8.2.2Renyi Entropy

8.2.3Adaptive Thresholding

8.3Region-Based Segmentation

8.3.1Watershed Segmentation

8.4Contour-Based Segmentation

8.4.1Chan-Vese Segmentation

8.5Segmentation Algorithm for Various Modalities

8.5.1Segmentation of Computed Tomography Image

8.5.2Segmentation of MRI Image

8.5.3Segmentation of Optical and Electron Microscope Images

8.6Summary

8.7Exercises

9Morphological Operations

9.1Introduction

9.2History

9.3Dilation

9.4Erosion

9.5Grayscale Dilation and Erosion

9.6Opening and Closing

9.7Grayscale Opening and Closing

9.8Hit-or-Miss

9.9Thickening and Thinning

9.9.1Skeletonization

9.10Summary

9.11Exercises

10Image Measurements

10.1Introduction

10.2Labeling

10.3Hough Transform

10.3.1Hough Line

10.3.2Hough Circle

10.4Template Matching

10.5Corner Detector

10.5.1FAST Corner Detector

10.5.2Harris Corner Detector

10.6Summary

10.7Exercises

11Neural Network

11.1Introduction

11.2Introduction

11.3Mathematical Modeling

11.3.1Forward Propagation

11.3.2Back-Propagation

11.4Graphical Representation

11.5Neural Network for Classification Problems

11.6Neural Network Example Code

11.7Summary

11.8Exercises

12Convolutional Neural Network

12.1Introduction

12.2Convolution

12.3Maxpooling

12.4LeNet Architecture

12.5Summary

12.6Exercises

IIIImage Acquisition

13X-Ray and Computed Tomography

13.1Introduction

13.2History

13.3X-Ray Generation

13.3.1X-Ray Tube Construction

13.3.2X-Ray Generation Process

13.4Material Properties

13.4.1Attenuation

13.4.2Lambert-Beer Law for Multiple Materials

13.4.3Factors Determining Attenuation

13.5X-Ray Detection

13.5.1Image Intensifier

13.5.2Multiple-Field II

13.5.3Flat Panel Detector (FPD)

13.6X-Ray Imaging Modes

13.6.1Fluoroscopy

13.6.2Angiography

13.7Computed Tomography (CT)

13.7.1Reconstruction

13.7.2Parallel-Beam CT

13.7.3Central Slice Theorem

13.7.4Fan-Beam CT

13.7.5Cone-Beam CT

13.7.6Micro-CT

13.8Hounsfield Unit (HU)

13.9Artifacts

13.9.1Geometric Misalignment Artifacts

13.9.2Scatter

13.9.3Offset and Gain Correction

13.9.4Beam Hardening

13.9.5Metal Artifacts

13.10Summary

13.11Exercises

14Magnetic Resonance Imaging

14.1Introduction

14.2Laws Governing NMR and MRI

14.2.1Faraday’s Law

14.2.2Larmor Frequency

14.2.3Bloch Equation

14.3Material Properties

14.3.1Gyromagnetic Ratio

14.3.2Proton Density

14.3.3T1 and T2 Relaxation Times

14.4NMR Signal Detection

14.5MRI Signal Detection or MRI Imaging

14.5.1Slice Selection

14.5.2Phase Encoding

14.5.3Frequency Encoding

14.6MRI Construction

14.6.1Main Magnet

14.6.2Gradient Magnet

14.6.3RF Coils

14.6.4K-Space Imaging

14.7T1, T2 and Proton Density Image

14.8MRI Modes or Pulse Sequence

14.8.1Spin Echo Imaging

14.8.2Inversion Recovery

14.8.3Gradient Echo Imaging

14.9MRI Artifacts

14.9.1Motion Artifact

14.9.2Metal Artifact

14.9.3Inhomogeneity Artifact

14.9.4Partial Volume Artifact

14.10Summary

14.11Exercises

15Light Microscopes

15.1Introduction

15.2Physical Principles

15.2.1Geometric Optics

15.2.2Numerical Aperture

15.2.3Diffraction Limit

15.2.4Objective Lens

15.2.5Point Spread Function (PSF)

15.2.6Wide-Field Microscopes

15.3Construction of a Wide-Field Microscope

15.4Epi-Illumination

15.5Fluorescence Microscope

15.5.1Theory

15.5.2Properties of Fluorochromes

15.5.3Filters

15.6Confocal Microscopes

15.7Nipkow Disk Microscopes

15.8Confocal or Wide-Field?

15.9Summary

15.10 Exercises

16Electron Microscopes

16.1Introduction

16.2Physical Principles

16.2.1Electron Beam

16.2.2Interaction of Electron with Matter

16.2.3Interaction of Electrons in TEM

16.2.4Interaction of Electrons in SEM

16.3Construction of EMs

16.3.1Electron Gun

16.3.2Electromagnetic Lens

16.3.3Detectors

16.4Specimen Preparations

16.5Construction of the TEM

16.6Construction of the SEM

16.7Factors Determining Image Quality

16.8Summary

16.9Exercises

AProcess-Based Parallelism using Joblib

A.1Introduction to Process-Based Parallelism

A.2Introduction to Joblib

A.3Parallel Examples

BParallel Programming using MPI4Py

B.1Introduction to MPI

B.2Need for MPI in Python Image Processing

B.3Introduction to MPI4Py

B.4Communicator

B.5Communication

B.5.1Point-to-Point Communication

B.5.2Collective Communication

B.6Calculating the Value of PI

CIntroduction to ImageJ

C.1Introduction

C.2ImageJ Primer

DMATLAB® and Numpy Functions

D.1Introduction

Bibliography

Index

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