Grid simulation services for the medical community

The first part of this paper presents a selection of medical simulation applications, including image reconstruction, near real-time registration for neuro-surgery, enhanced dose distribution calculation for radio-therapy, inhaled drug delivery prediction, plastic surgery planning and cardio-vascular system simulation. The latter two topics are discussed in some detail. In the second part, we show how such services can be made available to the clinical practitioner using Grid technology. We discuss the developments and experience made during the EU project GEMSS, which provides reliable, efficient, secure and lawful medical Grid services

Detection of Brain Injury Using Different Soft Computing Techniques: A Survey

The detection of brain injury is one of the important and difficult task in the field of medicine. If the brain injuries are not detected in time, then it can cause serious problems in patients and sometimes can even lead to death. Traumatic brain injury (TBI) is one of the major causes of mortality and poor quality of life among the survivors. Various imaging techniques are available for taking the images of the brain so that the injuries can be detected. Magnetic resonance imaging (MRI) is one of the common medical imaging technique used for the delineation of soft tissues such as that of the brain. This paper analyses few of the methods and their performances that have been proposed for the detection of the brain injury. In these methods different soft computing techniques such as artificial neural networks (ANN), k nearest neighbor (k-NN), support vector machine (SVM), Parzan window, etc. were used for the classification of abnormal and normal brain images. Before classification feature extraction and reduction were done using the methods such as DWT, GLCM, PCA, etc. DOI: 10.17762/ijritcc2321-8169.15030

Full modelling of high-intensity focused ultrasound and thermal heating in the kidney using realistic patient models

Objective: High-intensity focused ultrasound (HIFU) therapy can be used for non-invasive treatment of kidney (renal) cancer, but the clinical outcomes have been variable. In this study, the efficacy of renal HIFU therapy was studied using nonlinear acoustic and thermal simulations in three patients. Methods: The acoustic simulations were conducted with and without refraction in order to investigate its effect on the shape, size and pressure distribution at the focus. The values for the attenuation, sound speed, perfusion and thermal conductivity of the kidney were varied over the reported ranges to determine the effect of variability on heating. Furthermore, the phase aberration was studied in order to quantify the underlying phase shifts using a second order polynomial function. Results: The ultrasound field intensity was found to drop on average 11.1 dB with refraction and 6.4 dB without refraction. Reflection at tissue interfaces was found to result in a loss less than 0.1 dB. Focal point splitting due to refraction significantly reduced the heating efficacy. Perfusion did not have a large effect on heating during short sonication durations. Small changes in temperature were seen with varying attenuation and thermal conductivity, but no visible changes were present with sound speed variations. The aberration study revealed an underlying trend in the spatial distribution of the phase shifts. Conclusion: The results show that the efficacy of HIFU therapy in the kidney could be improved with aberration correction. Significance: A method is proposed by which patient specific pre-treatment calculations could be used to overcome the aberration and therefore make ultrasound treatment possible.Comment: Journal paper, IEEE Transactions on Biomedical Engineering (2018