Special issue on computational methods for biomedical image processing and analysis

Abstract

This special issue of the journal includes 11 articles related with biomedical image processing: two concern brain segmentation from MRI images; two of them use medical imaging to build patient customized 3D finite element models; one applies segmentation algorithms on CT images of the spine; one addresses the simulation of middle cerebral artery Doppler signals; two are related with the study of red blood cells from images; one uses classification procedures on cell tissue images; one addresses Monte Carlo simulations of PET imaging to estimate the activity correction according to patient specific weight; and a last one uses electromyography (EMG) and wavelet functions to study diabetic neuropathy in the lower limb muscles during gait. The main objective of this special issue on “Computational Methods for Biomedical Image Processing and Analysis” is to disseminate the recent advances in the related fields trying to identify widespread areas of potential collaboration among researchers of different sciences. The issue comprises 11 contributions from nine countries that were selected from 15 works previously presented at “III ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing (VipIMAGE 2011)”, that was held in Algarve, Portugal, in 12–14 October 2011 and particularly extended for this special issue. The articles included address different topics and applications related to Biomedical Image Processing and Analysis, including medical imaging, image segmentation, modeling and simulation, biomedical signal and image processing and analysis, biomechanics, 3D reconstruction, motion tracking and analysis, optimization, software developing, assisted diagnosis, and virtual reality. Computational methods of signal processing and analysis, particularly regarding 2D, 3D, and 4D images, have been commonly used in different applications of the human society. For instances, full automated or semi-automated systems based on Image Processing and Analysis algorithms have been increasing used in surveillance, recognition, inspection, human-machine interfaces, 3D vision and motion and deformation analysis. One of the main characteristics of Image Processing and Analysis domain is its inter-multidisciplinary. In fact, methodologies of several sciences, including Informatics, Mathematics, Statistics, Psychology, Mechanics, and Physics, can be usually found in this domain. Besides this inter-multidisciplinary, one of the main reasons that contributes for the continually effort performed in this domain of the human knowledge is the number of applications that can be easily found in medicine. For example, the use on medical images of statistical, geometrical, or physical-based procedures in order to model the imaged structures and achieve different goals, such as image segmentation, image registration, shape reconstruction, simulation, motion and deformation analysis, virtual reality, computer-assisted therapy, or tissue characterization.