Advanced computer vision approaches in biomedical image analysis.

Medical imaging is today becoming one of the most important visualization and interpretation methods in biology and medicine. The past decade has witnessed a tremendous development of new, powerful instruments for detecting, storing, transmitting, analyzing, and displaying images. These instruments are greatly amplifying the ability of biochemists, biologists, medical scientists, and physicians to see their objects of study and to obtain quantitative measurements to support scientific hypotheses and medical diagnoses. Noise, artifacts, and weak contrast are the cause of a decrease in image quality and make the interpretation of medical images very difficult. These sources of interference, which are of a different nature for mammograms than for ultrasound images, are responsible for the fact that conventional or traditional analysis and detection algorithms are not always successful. The biomedical imaging scene is one of the most challenging since we have to deal not only with non-Gaussian, nonstationary, and nonlinear processes (transients, bursts, and ruptures) but also with mixtures of components interacting in a quite complicated form. Therefore, much of the research done today is geared towards improvement of the reduced quality of the available biomedical imaging material.