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Processing and visualization of 3D medical data is nowadays a common problem. However, it remains challenging because the diversification and complexification of the available sources of information, as well as the specific requirements of clinicians, make it difficult to solve in a computer science point of view. Indeed, clinicians need ergonomic,(More)
In vivo imaging of the cardiac 3D fibre architecture is still a challenge, but it would have many clinical applications, for instance to better understand pathologies and to follow up remodelling after therapy. Recently, cardiac MRI enabled the acquisition of Diffusion Tensor images (DTI) of 2D slices. We propose a method for the complete 3D reconstruction(More)
Major advances in medical imaging raised the need for adapted methods and softwares. The recent emergence of diffusion tensor MRI (DT-MRI) was challenging since data produced by this modality are not simple grey-value images but complex diffusion tensor fields. Tensors are symmetric, positive definite matrices and suffer from a lack of adapted theoretical(More)
OBJECT The anterior commissure is a critical interhemispheric pathway in animals, yet its connections in humans are not clearly understood. Its distribution has shown to vary greatly between species, and it is thought that in humans it may convey axons from a larger territory than previously thought. The aim was to use an anatomical mapping tool to look at(More)
In vivo imaging of cardiac 3D fibre architecture is still a practical and methodological challenge. However it potentially provides important clinical insights, for example leading to a better understanding of the pathophysiology and the follow up of ventricular remodelling after therapy. Recently, the acquisition of 2D multi-slice Diffusion Tensor Images(More)
Processing and visualisation of dynamic data is still a common challenge in medical imaging, especially as for many applications there is an increasing amount of clinical data as well as generated data, such as in cardiac modelling. In this context, there is a strong need for software that can deal with dynamic data of different kinds (i.e. images, meshes,(More)
Neuroimaging biomarkers play a prominent role for disease diagnosis or tracking neurodegenerative processes. Multiple methods have been proposed by the community to extract robust disease specific markers from various imaging modalities. Evaluating the accuracy and robustness of developed methods is difficult due to the lack of a biologically realistic(More)
This paper presents an extension of the Visualization ToolKit dedicated to spatiotemporal data synchronization , visualization and management. It basically consists in a versatile library providing func-tionalities to help developers setting up sophisticated applications with minimal development effort. In the medical imaging context, various types of data(More)
Multi-modal, multi-parametric Magnetic Resonance (MR) Imaging is becoming an increasingly sophisticated tool for neuroimaging. The relationships between parameters estimated from different individual MR modalities have the potential to transform our understanding of brain function, structure, development and disease. This article describes a new software(More)