There was a time not so long ago, well within the memory of many of us, when medical imaging was an analog process in which X-rays, or reflected ultrasound signals, exiting from a patient were intercepted by a detector, and their intensity depicted as bright spots on a fluorescent screen or dark areas in a photographic film. The linkage between the exiting radiation and the resulting image was direct, and the process of forming the image was easily understandable and controllable. Teaching this process was straightforward, and learning how the process worked was relatively easy.
In the 1960s, digital computers began to migrate slowly into medical imaging, but the transforming event was the introduction of X-ray computed tomography (CT) into medical imaging in the early 1970s.With CT, the process of detecting radiation exiting from the patient was separated from the process of forming and displaying an image by a multitude of computations that only a computer could manage. The computations were guided by mathematical algorithms that reconstructed X-ray images from a large number of X-ray measurements across multiple imaging planes (projections) obtained at many different angles. X-ray CT not only provided entirely new ways to visualize human anatomy; it also presaged the introduction of digital imaging methods to every imaging technique employed in medicine, and ushered the way for new imaging technologies such as magnetic resonance and optical imaging.
Digital imaging permits image manipulations such as edge enhancement, contrast improvement and noise suppression, facilitates temporal and energy subtraction of images, and speeds the development of hybrid imaging systems in which two (or more) imaging methods can be deployed on the same gantry and without moving the patient. The production and manipulation of digital images are referred to collectively as imaging processing.
Without question, the separation of signal detection from image display offers many advantages, including the ability to optimize each process independently of the other. However, it also presents a major difficulty, namely that to many persons involved in imaging, the computational processes between detection and display are mysterious operations that are the province of physicists and engineers. Physicians, technologists and radiological science students are expected to accept the validity of the images produced by a mysterious ‘black box’ between signal input and image output without really understanding how the images are formed from input signals.
A plethora of text and reference books, review articles and scientific manuscripts have been written to describe the mechanisms and applications of the various mathematical algorithms that are used in image processing. These references are interpretable by the mathematical cognoscenti, but are of little help to most persons who lack the mathematical sophistication of physicists and engineers. What is needed is a text that explains image processing without advanced mathematics so that the reader can gain an intuitive feel for what occurs between signal detection and image display. Such a text would be a great help to many who want to understand how images are formed, manipulated and displayed but who do not have the background needed to understand the mathematical algorithms used in this process.
Some notable features of this book are:
- Scope: It focuses on medical imaging.
- Approach: The approach is intuitive rather than mathematical.
- Emphasis: The concept of spatial frequency is the core of the text.
- Practice: Most of the concepts and methods described can be demonstrated and practiced with the free public-domain software Image.
- Revision: Major parts can be revised by studying just the figures and their captions.
Radiographers, radiation therapists, and nuclear medicine technologists routinely acquire, process, transmit and store images usingmethods and systems developed by engineers and computer scientists. Mostly they don’t need to understand the details of the maths involved. However, everyone does their job better, and has a better chance of improving the way their job is done, when they understand the tools they use at the deepest possible level. This book tries to dig as deep as possible into imaging theory without using maths.
Contents
1 Introduction
1.1 What Is This Book Trying To Do?
1.2 Chapter Outline
1.2.1 Digital Images
1.2.2 Medical Images
1.2.3 The Spatial and Frequency Domains
1.2.4 Image Quality
1.2.5 Contrast Adjustment
1.2.6 Image Filters
1.2.7 Spatial Transformations
1.2.8 Appendices
1.3 Revision
1.4 Practical Image Processing
1.4.1 Images for Teaching
2 Digital Images
2.1 Introduction
2.2 Defining a Digital Image
2.3 Image Information
2.3.1 Pixels
2.3.2 Image Size, Scale, and Resolution
2.3.3 Pixel Information
2.3.4 Ways of Representing Numbers
2.3.5 Data Accuracy
2.4 Image Metadata
2.4.1 Metadata Content
2.4.2 Lookup Tables
2.5 Image Storage
2.5.1 Image File Formats
2.5.2 Image Data Compression Methods
2.6 Summary
3 Medical Images
3.1 Introduction
3.2 The Energetics of Imaging
3.2.1 Radio Frequencies
3.3 Spatial and Temporal Resolution of Medical Images
3.4 Medical Imaging Methods
3.4.1 Magnetic Resonance
3.4.2 Visible Light Imaging
3.4.3 X-Ray Imaging
3.4.4 Emission Imaging
3.4.5 Portal Images
3.4.6 Ultrasonography
3.5 Summary
4 The Spatial and Frequency Domains
4.1 Introduction
4.2 Images in the Spatial and Frequency Domains
4.2.1 The Spatial Domain
4.2.2 Common All-Garden Temporal Frequency
4.2.3 The Concept of Spatial Frequency
4.2.4 The Cosine and Hartley Transforms
4.3 Fourier Transforms and Fourier Spectra
4.3.1 1D Fourier Transforms
4.3.2 2D Fourier Transforms
4.3.3 Fourier Spectra
4.3.4 The Zero Frequency or ‘DC’ Term
4.3.5 Fourier Spectra of More Complex Images
4.3.6 How Many Spatial Frequencies are Needed?
4.3.7 Fourier Spectra of Lines
4.4 The Complex Data Behind Fourier Spectra
4.5 Two Practical Applications of Fourier Transforms
4.5.1 How Does the Focal Spot of an X-Ray Tube Affect Image Resolution?
4.5.2 Making Diagnostic Images from Raw MRI Data
4.6 Summary
5 Image Quality
5.1 Introduction
5.2 Contrast
5.2.1 Simple Measures of Contrast
5.2.2 Contrast and Spatial Frequency
5.2.3 Optimizing Contrast
5.3 Image Noise
5.3.1 What Is Noise?
5.3.2 Quantum Mottle
5.3.3 Other Noises
5.3.4 Signal to Noise Ratio
5.4 Contrast + Noise
5.5 Spatial Resolution
5.5.1 Line Pairs
5.5.2 The Modulation Transfer Function
5.5.3 The Edge, Line, and Point Spread Functions
5.6 Contrast + Noise + Resolution
5.7 Summary
6 Contrast Adjustment
6.1 Introduction
6.2 Human Visual Perception
6.3 Histograms
6.4 Manual Contrast Adjustment
6.4.1 Contrast Stretching
6.4.2 Window and Level
6.4.3 Nonlinear Mapping Functions
6.5 Automatic Contrast Adjustment
6.5.1 Normalization
6.5.2 Histogram Equalization
6.5.3 Histogram Specification
6.5.4 Region-Specific Contrast Adjustments
6.5.5 Binary Contrast Enhancement – Thresholding
6.5.6 Hardware Contrast
6.6 Practical Example. Adjusting the Contrast of a Magnetic Resonance Microimage
6.7 Summary
7 Image Filters
7.1 Introduction
7.2 Frequency Domain Filters
7.2.1 Ideal Filters
7.2.2 Butterworth Filters
7.2.3 Gaussian Filters
7.2.4 Band Stop Filters
7.2.5 Band Pass Filters
7.2.6 Directional Filters
7.3 Spatial Domain Filters
7.3.1 Smoothing and Blurring
7.3.2 Gradients and Edges
7.3.3 Spatial and Frequency Domain Properties of Convolution
7.3.4 Convolution Versus Correlation
7.3.5 Median Filters
7.3.6 Adaptive Filters
7.4 Summary
8 Spatial Transformation
8.1 Introduction
8.2 Translation
8.3 Rotation
8.4 Interpolation
8.4.1 Nearest-Neighbor
8.4.2 Bilinear
8.4.3 Bicubic
8.5 Resizing Images
8.6 Summary
A ImageJ
A.1 General
A.1.1 Installation of ImageJ
A.1.2 Documentation
A.1.3 Plugins
A.2 Getting Started
A.3 Basic Image Operations
A.4 Installing Macro Plugins
A.5 Further Reading
B A Note on Precision and Accuracy
C Complex Numbers
C.1 What Is a Complex Number?
C.2 Manipulating Complex Numbers
C.3 Alternating Currents
C.4 MRI
Index
Book Details
- Paperback: 216 pages
- Publisher: Springer; 1st edition
- Language: English
- ISBN-10: 1848820860
- ISBN-13: 978-1848820869
- Product Dimensions: 9.2 x 6.1 x 0.4 inches