In the clinical domain, signal and image processing algorithms aiming at extracting information, quantifying processes, or improving the visualization of medical data have exploded. They are now commonly used for research activities or in clinical routines, for the diagnosis or treatment of many pathologies. New algorithms overcoming the existing ones by their better computational cost or by providing additional or more accurate information are still proposed. Moreover, new applications for the new and existing algorithms emerge. This is true for any kind of medical data but the physiological and pathophysiological questions offer a variety of applications and situations. This includes the study and understanding of adaptive responses in health and pathophysiological mechanisms in disease, at any level of physiological organization, ranging from molecules to humans. Moreover, adaptive, integrative, and translational physiology is concerned.

This special issue is intended to present and discuss signal and image processing algorithms (linear/nonlinear analysis) and their application to physiological data. It also aims at facilitating the exchange of ideas and promoting interactions between investigators across different specialties. Papers dealing with signal/image processing work at the molecular level, at the level of the cell membrane, single cells, tissues, or organs, and on systems physiology are considered. Moreover, human physiology under a variety of physiological and pathophysiological conditions is acceptable in the following domains: vascular physiology, environmental and exercise physiology, muscle physiology, renal physiology, respiratory physiology, cardiac electrophysiology, and autonomic neuroscience.

We invite investigators to contribute to this special issue by submitting reviews and original papers.

Potential topics include, but are not limited to:

• Linear and nonlinear analysis of physiological time series
• Filtering and restoration enhancement
• Image segmentation
• Pattern recognition
• Feature extraction, description, and interpretation
• Image texture analysis
• Image representation and rendering
• Multispectral processing
• Data coding and compression
• Image quality assessment
• 1D, 2D, and 3D modeling and processing
• Methods in diagnosis or treatment optimization