Image Processing and Acquisition Using Python : Applications to Medicine and Biology
[Book Description]
Image Processing and Acquisition using Python provides readers with a sound foundation in both image acquisition and image processing-one of the first books to integrate these topics together. By improving readers' knowledge of image acquisition techniques and corresponding image processing, the book will help them perform experiments more effectively and cost efficiently as well as analyze and measure more accurately. Long recognized as one of the easiest languages for non-programmers to learn, Python is used in a variety of practical examples. A refresher for more experienced readers, the first part of the book presents an introduction to Python, Python modules, reading and writing images using Python, and an introduction to images. The second part discusses the basics of image processing, including pre/post processing using filters, segmentation, morphological operations, and measurements. The last part describes image acquisition using various modalities, such as x-ray, CT, MRI, light microscopy, and electron microscopy. These modalities encompass most of the common image acquisition methods currently used by researchers in academia and industry.
[Table of Contents]
List of Figures xvii
List of Tables xxiii
Foreword xxv
Preface xxvii
Introduction xxxi
About the Authors xxxiii
List of Symbols and Abbreviations xxxv
I Introduction to Images and Computing using 1 (54)
Python
1 Introduction to Python 3 (20)
1.1 Introduction 3 (1)
1.2 What is Python? 4 (1)
1.3 Python Environments 5 (3)
1.3.1 Python Interpreter 6 (1)
1.3.2 Enthought Python Distribution 6 (1)
(EPD)
1.3.3 PythonXY 7 (1)
1.4 Running a Python Program 8 (1)
1.5 Basic Python Statements and Data Types 8 (11)
1.5.1 Data Structures 11 (8)
1.6 Summary 19 (1)
1.7 Exercises 20 (3)
2 Computing using Python Modules 23 (14)
2.1 Introduction 23 (1)
2.2 Python Modules 23 (3)
2.2.1 Creating Modules 24 (1)
2.2.2 Loading Modules 24 (2)
2.3 Numpy 26 (5)
2.3.1 Numpy Array or Matrices? 30 (1)
2.4 Scipy 31 (1)
2.5 Matplotlib 32 (1)
2.6 Python Imaging Library 33 (1)
2.7 Scikits 33 (1)
2.8 Python OpenCV Module 34 (1)
2.9 Summary 34 (1)
2.10 Exercises 35 (2)
3 Image and its Properties 37 (18)
3.1 Introduction 37 (1)
3.2 Image and its Properties 38 (6)
3.2.1 Bit Depth 38 (1)
3.2.2 Pixel and Voxel 39 (2)
3.2.3 Image Histogram 41 (1)
3.2.4 Window and Level 42 (1)
3.2.5 Connectivity: 4 or 8 Pixels 43 (1)
3.3 Image Types 44 (5)
3.3.1 JPEG 44 (1)
3.3.2 TIFF 44 (1)
3.3.3 DICOM 45 (4)
3.4 Data Structures for Image Analysis 49 (2)
3.4.1 Reading Images 49 (1)
3.4.2 Displaying Images 50 (1)
3.4.3 Writing Images 50 (1)
3.5 Programming Paradigm 51 (2)
3.6 Summary 53 (1)
3.7 Exercises 53 (2)
II Image Processing using Python 55 (152)
4 Spatial Filters 57 (32)
4.1 Introduction 57 (1)
4.2 Filtering 58 (11)
4.2.1 Mean Filter 60 (4)
4.2.2 Median Filter 64 (2)
4.2.3 Max Filter 66 (2)
4.2.4 Min Filter 68 (1)
4.3 Edge Detection using Derivatives 69 (16)
4.3.1 First Derivative Filters 71 (8)
4.3.2 Second Derivative Filters 79 (6)
4.4 Summary 85 (1)
4.5 Exercises 86 (3)
5 Image Enhancement 89 (20)
5.1 Introduction 89 (1)
5.2 Pixel Transformation 89 (2)
5.3 Image Inverse 91 (1)
5.4 Power Law Transformation 92 (5)
5.5 Log Transformation 97 (2)
5.6 Histogram Equalization 99 (4)
5.7 Contrast Stretching 103 (3)
5.8 Summary 106 (1)
5.9 Exercises 107 (2)
6 Fourier Transform 109 (30)
6.1 Introduction 109 (1)
6.2 Definition of Fourier Transform 110 (3)
6.3 Two-Dimensional Fourier Transform 113 (5)
6.3.1 Fast Fourier Transform using 115 (3)
Python
6.4 Convolution 118 (2)
6.4.1 Convolution in Fourier Space 119 (1)
6.5 Filtering in Frequency Domain 120 (17)
6.5.1 Ideal Lowpass Filter 120 (3)
6.5.2 Butterworth Lowpass Filter 123 (2)
6.5.3 Gaussian Lowpass Filter 125 (2)
6.5.4 Ideal Highpass Filter 127 (3)
6.5.5 Butterworth Highpass Filter 130 (2)
6.5.6 Gaussian Highpass Filter 132 (2)
6.5.7 Bandpass Filter 134 (3)
6.6 Summary 137 (1)
6.7 Exercises 138 (1)
7 Segmentation 139 (26)
7.1 Introduction 139 (1)
7.2 Histogram Based Segmentation 139 (12)
7.2.1 Otsu's Method 141 (3)
7.2.2 Renyi Entropy 144 (5)
7.2.3 Adaptive Thresholding 149 (2)
7.3 Region Based Segmentation 151 (10)
7.3.1 Watershed Segmentation 153 (8)
7.4 Segmentation Algorithm for Various 161 (1)
Modalities
7.4.1 Segmentation of Computed 161 (1)
Tomography Image
7.4.2 Segmentation of MRI Image 161 (1)
7.4.3 Segmentation of Optical and 162 (1)
Electron Microscope Image
7.5 Summary 162 (1)
7.6 Exercises 163 (2)
8 Morphological Operations 165 (24)
8.1 Introduction 165 (1)
8.2 History 165 (1)
8.3 Dilation 166 (5)
8.4 Erosion 171 (4)
8.5 Grayscale Dilation and Erosion 175 (1)
8.6 Opening and Closing 176 (3)
8.7 Hit-or-Miss 179 (5)
8.8 Thickening and Thinning 184 (2)
8.8.1 Skeletonization 185 (1)
8.9 Summary 186 (1)
8.10 Exercises 187 (2)
9 Image Measurements 189 (18)
9.1 Introduction 189 (1)
9.2 Labeling 189 (5)
9.3 Hough Transform 194 (7)
9.3.1 Hough Line 194 (3)
9.3.2 Hough Circle 197 (4)
9.4 Template Matching 201 (4)
9.5 Summary 205 (1)
9.6 Exercises 205 (2)
III Image Acquisition 207 (106)
10 X-Ray and Computed Tomography 209 (38)
10.1 Introduction 209 (1)
10.2 History 209 (1)
10.3 X-Ray Generation 210 (6)
10.3.1 X-Ray Tube Construction 210 (2)
10.3.2 X-Ray Generation Process 212 (4)
10.4 Material Properties 216 (3)
10.4.1 Attenuation 216 (2)
10.4.2 Lambert Beer Law for Multiple 218 (1)
Materials
10.5 X-Ray Detection 219 (5)
10.5.1 Image Intensifier 220 (1)
10.5.2 Multiple-Field II 221 (2)
10.5.3 Flat Panel Detector (FPD) 223 (1)
10.6 X-Ray Imaging Modes 224 (2)
10.6.1 Fluoroscopy 224 (1)
10.6.2 Angiography 224 (2)
10.7 Computed Tomography (CT) 226 (10)
10.7.1 Reconstruction 227 (1)
10.7.2 Parallel Beam CT 227 (1)
10.7.3 Central Slice Theorem 228 (4)
10.7.4 Fan Beam CT 232 (1)
10.7.5 Cone Beam CT 233 (1)
10.7.6 Micro-CT 234 (2)
10.8 Hounsfield Unit (HU) 236 (1)
10.9 Artifacts 237 (6)
10.9.1 Geometric Misalignment Artifacts 238 (1)
10.9.2 Scatter 238 (2)
10.9.3 Offset and Gain Correction 240 (1)
10.9.4 Beam Hardening 241 (1)
10.9.5 Metal Artifacts 242 (1)
10.10 Summary 243 (1)
10.11 Exercises 244 (3)
11 Magnetic Resonance Imaging 247 (28)
11.1 Introduction 247 (1)
11.2 Laws Governing NMR and MRI 248 (3)
11.2.1 Faraday's Law 248 (1)
11.2.2 Larmor Frequency 249 (1)
11.2.3 Bloch Equation 250 (1)
11.3 Material Properties 251 (4)
11.3.1 Gyromagnetic Ratio 251 (1)
11.3.2 Proton Density 252 (1)
11.3.3 T1 and T2 Relaxation Times 253 (2)
11.4 NMR Signal Detection 255 (1)
11.5 MRI Signal Detection or MRI Imaging 256 (3)
11.5.1 Slice Selection 258 (1)
11.5.2 Phase Encoding 258 (1)
11.5.3 Frequency Encoding 259 (1)
11.6 MRI Construction 259 (4)
11.6.1 Main Magnet 259 (1)
11.6.2 Gradient Magnet 260 (1)
11.6.3 RF Coils 261 (1)
11.6.4 K-Space Imaging 262 (1)
11.7 T1, T2 and Proton Density Image 263 (2)
11.8 MRI Modes or Pulse Sequence 265 (3)
11.8.1 Spin Echo Imaging 265 (1)
11.8.2 Inversion Recovery 266 (1)
11.8.3 Gradient Echo Imaging 267 (1)
11.9 MRI Artifacts 268 (4)
11.9.1 Motion Artifact 269 (2)
11.9.2 Metal Artifact 271 (1)
11.9.3 Inhomogeneity Artifact 271 (1)
11.9.4 Partial Volume Artifact 272 (1)
11.10 Summary 272 (1)
11.11 Exercises 273 (2)
12 Light Microscopes 275 (20)
12.1 Introduction 275 (1)
12.2 Physical Principles 276 (6)
12.2.1 Geometric Optics 276 (1)
12.2.2 Numerical Aperture 277 (1)
12.2.3 Diffraction Limit 278 (2)
12.2.4 Objective Lens 280 (1)
12.2.5 Point Spread Function (PSF) 281 (1)
12.2.6 Wide-Field Microscopes 282 (1)
12.3 Construction of a Wide-Field 282 (2)
Microscope
12.4 Epi-Illumination 284 (1)
12.5 Fluorescence Microscope 284 (4)
12.5.1 Theory 284 (1)
12.5.2 Properties of Fluorochromes 285 (2)
12.5.3 Filters 287 (1)
12.6 Confocal Microscopes 288 (1)
12.7 Nipkow Disk Microscopes 289 (2)
12.8 Confocal or Wide-Field? 291 (1)
12.9 Summary 292 (1)
12.10 Exercises 293 (2)
13 Electron Microscopes 295 (18)
13.1 Introduction 295 (1)
13.2 Physical Principles 296 (5)
13.2.1 Electron Beam 297 (1)
13.2.2 Interaction of Electron with 298 (1)
Matter
13.2.3 Interaction of Electrons in TEM 299 (1)
13.2.4 Interaction of Electrons in SEM 300 (1)
13.3 Construction of EM 301 (5)
13.3.1 Electron Gun 301 (2)
13.3.2 Electromagnetic Lens 303 (1)
13.3.3 Detectors 304 (2)
13.4 Specimen Preparations 306 (1)
13.5 Construction of TEM 307 (1)
13.6 Construction of SEM 308 (1)
13.7 Summary 309 (2)
13.8 Exercises 311 (2)
A Installing Python Distributions 313 (10)
A.1 Windows 313 (5)
A.1.1 PythonXY 313 (3)
A.1.2 Enthought Python Distribution 316 (1)
A.1.3 Updating or Installing New Modules 316 (2)
A.2 Mac or Linux 318 (5)
A.2.1 Enthought Python Distribution 318 (1)
A.2.2 Installing New Modules 318 (5)
B Parallel Programming Using MPI4Py 323 (10)
B.1 Introduction to MPI 323 (1)
B.2 Need for MPI in Python Image 324 (1)
Processing
B.3 Introduction to MPI4Py 325 (1)
B.4 Communicator 326 (1)
B.5 Communication 327 (4)
B.5.1 Point-to-Point Communication 327 (2)
B.5.2 Collective Communication 329 (2)
B.6 Calculating the Value of PI 331 (2)
C Introduction to ImageJ 333 (4)
C.1 Introduction 333 (1)
C.2 ImageJ Primer 334 (3)
D MATLAB® and Numpy Functions 337 (4)
D.1 Introduction 337 (4)
Bibliography 341 (10)
Index 351
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