Biomedical Image Processing, Modelling and Simulation

Thousands of publications have been published on diverse image analysis issues such as segmentation, registration, visualization, quantification, object tracking, and detection, making biomedical image analysis an important study field in biomedical research. For a long time, the authors' own data sets were used to validate and evaluate new methods, making a fair and direct comparison of the solutions difficult. Biomedical imaging has evolved from early, simple uses of X-rays for fracture diagnosis and foreign body detection to a collection of powerful techniques that can be used not only for patient care but also for studying biological structure and function and addressing fundamental biomedical questions. Digital radiography, X-ray computed tomography (CT), nuclear (including positron emission tomography (PET)), ultrasound, optical, and magnetic resonance imaging (MRI) have all evolved into a variety of non-invasive technologies for probing complete 3-dimensional bodies. In the realm of biomedical image analysis, difficulties are becoming increasingly important, encompassing a wide range of topics, method classes, and imaging modalities. Biomedical imaging is a valuable tool for visualizing the body's internal organs and diseases. The imaging capabilities available today provide for unprecedented views of biological processes.