BRIAN (Brain image analysis): A toolkit for the analysis of multimodal brain datasets

The analysis of cognitive processes in man usually involves multiple examina­tion modalities which map different aspects of the brain. Among these proce­dures, at least one modality yielding anatomical information (i.e. MRI*) besidesone or more functional modalities (fMRI, PET, SPECT, EEG, MEG) are involved.Because these different examination methods yield complimentary informationabout the anatomical, metabolical and neurophysiological state of the brain, acombined data evaluation is highly desirable and will lead to results not achiev­able within one examination domain.Such studies are of importance in research (cognitive neuroscience) and ­ withan emphasis on pathological processes ­ in clinical disciplines like neurology,neurosurgery and psychiatry.We have developed a program package for the handling of image datasets(MRI, PET, SPECT, CCT) and signal datasets (EEG, MEG) which allows a com­bined analysis of these data sources in a four­dimensional coordinate space (x, y,z, and time)

Adaptive transfer functions: improved multiresolution visualization of medical models

The final publication is available at Springer via http://dx.doi.org/10.1007/s00371-016-1253-9Medical datasets are continuously increasing in size. Although larger models may be available for certain research purposes, in the common clinical practice the models are usually of up to 512x512x2000 voxels. These resolutions exceed the capabilities of conventional GPUs, the ones usually found in the medical doctors’ desktop PCs. Commercial solutions typically reduce the data by downsampling the dataset iteratively until it fits the available target specifications. The data loss reduces the visualization quality and this is not commonly compensated with other actions that might alleviate its effects. In this paper, we propose adaptive transfer functions, an algorithm that improves the transfer function in downsampled multiresolution models so that the quality of renderings is highly improved. The technique is simple and lightweight, and it is suitable, not only to visualize huge models that would not fit in a GPU, but also to render not-so-large models in mobile GPUs, which are less capable than their desktop counterparts. Moreover, it can also be used to accelerate rendering frame rates using lower levels of the multiresolution hierarchy while still maintaining high-quality results in a focus and context approach. We also show an evaluation of these results based on perceptual metrics.Peer ReviewedPostprint (author's final draft

Qualitative grading of aortic regurgitation: a pilot study comparing CMR 4D flow and echocardiography.

Over the past 10 years there has been intense research in the development of volumetric visualization of intracardiac flow by cardiac magnetic resonance (CMR).This volumetric time resolved technique called CMR 4D flow imaging has several advantages over standard CMR. It offers anatomical, functional and flow information in a single free-breathing, ten-minute acquisition. However, the data obtained is large and its processing requires dedicated software. We evaluated a cloud-based application package that combines volumetric data correction and visualization of CMR 4D flow data, and assessed its accuracy for the detection and grading of aortic valve regurgitation using transthoracic echocardiography as reference. Between June 2014 and January 2015, patients planned for clinical CMR were consecutively approached to undergo the supplementary CMR 4D flow acquisition. Fifty four patients(median age 39 years, 32 males) were included. Detection and grading of the aortic valve regurgitation using CMR4D flow imaging were evaluated against transthoracic echocardiography. The agreement between 4D flow CMR and transthoracic echocardiography for grading of aortic valve regurgitation was good (j = 0.73). To identify relevant,more than mild aortic valve regurgitation, CMR 4D flow imaging had a sensitivity of 100 % and specificity of 98 %. Aortic regurgitation can be well visualized, in a similar manner as transthoracic echocardiography, when using CMR 4D flow imaging

The volume in focus: hardwareassisted focus and context effects for volume visualization

In many volume visualization applications there is some region of specific interest where we wish to see fine detail - yet we do not want to lose an impression of the overall picture. In this research we apply the notion of focus and context to texture-based volume rendering. A framework has been developed that enables users to achieve fast volumetric distortion and other effects of practical use. The framework has been implemented through direct programming of the graphics processor and integrated into a volume rendering system. Our driving application is the effective visualization of aneurysms, an important issue in neurosurgery. We have developed and evaluated an easy-to-use system that allows a neurosurgicalteam to explore the nature of cerebral aneurysms, visualizing the aneurysm itself in fine detail while still retaining a view of the surrounding vasculature

Computational medical imaging for total knee arthroplasty using visualitzation toolkit

This project is presented as a Master Thesis in the field of Civil Engineering, Biomedical specialization. As the project of an Erasmus exchange student, this thesis has been under supervision both the Universite Livre de Bruxelles and the Universitat Politecnica de Catalunya. The purpose of this thesis to put in practice all the knowledges acquired during this Master in Industrial Engineering in UPC and to be a support for medical staff in total knee arthoplasty procedures. Prof. Emmanuel Thienpont has been working for years as orthopaedic surgeon at the Hospital Sant Luc, Brussels. His years of work and research have been mainly focused on Total Knee Arthroplasty or TKA. During one of the most important steps of this procedure, the orthopaedic surgeon has to cut the head of the femur following two perpendicular cutting planes. Nevertheless, the orientation of these planes are directly dependant of the femur constitution. This Master Thesis has been conceived in order to offer the surgeon a tool to determine the proper direction planes in a previous step before the surgical procedure. This project pretends to give the surgeon an openfree computational platform to access to patient geometrical and physiological information before involving the subject in any invasive procedure