Biomedical Signal and Image Processing

TLDR

Biological signal and image processing (BSIP) is a central field in biomedical engineering that enhances physiological knowledge, supports diverse clinical procedures, and integrates information across multiple signals, organs, modalities, and scales using advanced time‑frequency, time‑variant, and nonlinear dynamical methods. This article emphasizes the critical links and synergies between BSIP and physiological modeling. The authors illustrate these connections with examples from cardiovascular studies, neurosciences, and functional imaging employing various modalities. They report that electromagnetic field signals and images, when properly detected, have significant impacts on several biomedical applications.

Abstract

Biological signal and image processing (BSIP) constitutes a major field of interest in both educational aspects and research environments in biomedical engineering. In fact, the physiological knowledge improvement in a wide variety of innovative research as well as the implementation in many clinical procedures extensively makes use of these concepts in more or less sophisticated medical applications. In this article, the important links between BSIP and physiological modeling and their important derived synergies are particularly stressed. In support of this aim, examples have been provided in the areas of cardiovascular system studies, as well as in neurosciences and functional imaging, by using different modalities. Along this direction, the integration operation of the detected information between multiple signals, organs, modalities, and across multiple scales (from gene/protein levels up to cell and organ levels) seems to be extremely promising. Further, advanced methods in the area of information treatment, such as time-frequency and time-variant approaches, have been investigated in the biomedical field together with the complexity measurements, most often carried out through nonlinear dynamical approaches where, also in this context, the integration between modeling and information processing plays a fundamental role. Finally, a few examples have been described in which the study of EMFs, in the form of signals and images properly detected, have a relevant impact on various biomedical applications.