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Introduction
I.3 BRIEF DESCRIPTION OF CHAPTERS
As mentioned previously, the book is divided into three parts. Part I gives an introduction to digital signal and image processing techniques. Chapter 1 explains the
main fundamental concepts of signal processing in simple conceptual language. This
chapter introduces the main signal processing concepts and tools in nonmathematical terms to prepare the readers for a more rigorous description of these concepts in
the following chapters. Chapter 2 describes the definition and applications of continuous and digital Fourier transform. All concepts and definitions in this chapter are
explained using a number of examples to ensure that the reader is not overwhelmed
by the mathematical formulae. More specifically, as demonstrated in Chapter 2 as
well as in subsequent chapters, the authors feel strongly that the description of the
mathematical formulation of various signal and image processing methods must be
accompanied by elaborate conceptual explanations.
Chapter 3 discusses different techniques for filtering, enhancement, and restoration of images. Even though the techniques are described mainly for images, the
applications of some of these techniques in the processing of one-dimensional signals
are also described. In Chapter 4, different techniques for edge detection and segmentation of digital images are discussed. Chapter 5 is devoted to wavelet transforms
and their main signal and image processing applications. Other advanced signal and
image processing techniques, including the basic concepts of stochastic processes and
information theory, are discussed in Chapter 6. Chapter 7, the last chapter in Part I,
provides an introduction to pattern recognition methods, including classification and
clustering techniques.
Part II describes the main one-dimensional biomedical signals and the processing
techniques applied to analyze these signals. Chapter 8 provides a concise review of
the electrical activities of the cell. Since all electrical signals of the human body are
somehow created by action potential, this chapter acts as an introduction to the rest
of the chapters in Part II.
Chapters 9 through 11 are devoted to analysis and processing of the main biomedical signals, i.e., electrocardiogram (ECG), electroencephalogram (EEG), and electromyogram (EMG). In each case, the biological origins of the signal, together with its
main applications in biomedical diagnostics, are described. Then, different techniques
to process each signal and extract important features from it are discussed. In addition, the main diseases that are often detected and diagnosed using each of the signals
are briefly introduced, and the computational techniques applied to detect such diseases from the signals are described. In Chapter 12, other biomedical signals (including blood pressure, electrooculogram, and magnetoencephalogram) are discussed. All
the chapters in this part have practical examples and exercises (with biomedical data)
to help students gain hands-on experience in analyzing biomedical signals.
In Part III, the physical and physiological principles, formation, and importance of
the main biomedical imaging modalities are discussed. The various processing techniques applied to analyze different types of biomedical images are also covered in this
part. In Chapter 13, the principal ideas and formulations of computed tomography
(CT) are presented. These techniques are essential in understanding many biomedical imaging systems and technologies such as x-ray CT, MRI, PET, and ultrasound.