Foundations of Medical Imaging and Signal Recording - Biomedical Signal Analysis: Contemporary Methods and Applications - page 3

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Foundations of Medical Imaging and Signal
Recording

Computer processing and analysis of medical images, as well as experi-
mental data analysis of physiological signals, have evolved since the late
1980s from a variety of directions, ranging from signal and imaging ac-
quisition equipment to areas such as digital signal and image processing,
computer vision, and pattern recognition.
The most important physiological signals, such as electrocardiograms
(ECG), electromyograms (EMG), electroencephalograms (EEG), and
magnetoencephalograms (MEG), represent analog signals that are digi-
tized for the purposes of storage and data analysis.
The nature of medical images is very broad; it is as simple as an
chest X-ray or as sophisticated as noninvasive brain imaging, such as
functional magnetic resonance imaging (fMRI).
While medical imaging is concerned with the interaction of all forms
of radiation with tissue and the clinical extraction of relevant informa-
tion, its analysis encompasses the measurement of anatomical and phys-
iological parameters from images, image processing, and motion and
change detection from image sequences.
This chapter gives an overview of biological signal and image analy-
sis, and describes the basic model for computer-aided systems as a com-
mon basis enabling the study of several problems of medical-imaging-
based diagnostics.

1.1 Biosignal Recording

Biosignals represent space-time records with one or multiple independent
or dependent variables that capture some aspect of a biological event.
They can be either deterministic or random in nature. Deterministic
signals very often can be compact, described by syntactic techniques,
while random signals are mainly described by statistical techniques.
In this section, we will present the most common biosignals and the
events from which they were generated. Table 1.1 describes these signals.
Biosignals are usually divided into the following groups:

• Bioelectrical (electrophysiological) signals: Electrical and chemical

transmissions form the electrophysiological communication between neu-