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A universal unanswered question in neuroscience and machine learning is whether computers can decode the patterns of the human brain. Multi-Voxel Pattern Analysis (MVPA) is a critical tool for addressing this question. However, there are two challenges in the previous MVPA methods, which include decreasing sparsity and noise in the extracted features and increasing the performance of prediction. In...
In fluoroscopic tracking for fractured femur bone fixation, a precise identification of the femoral head provides valuable guidance for positioning the implant instruments such as nails and screws. Noise, occlusions and weak edges challenge the task of automatically segmenting the femoral head. In this paper, a fast and fully automated method to precisely delineate the femoral head in fluoroscopic...
This work presents the first steps towards the development and implementation of a novel 3D biomechanical-based method for assessing the viability of myocardial tissue, with particular interest for its application in myocardial infarction (MI) diagnosis. This assessment technique quantifies the myocardial contraction forces developed within the ventricular myofibrils in response to the electrophysiological...
This work presents the first steps towards the development and implementation of a novel 3D biomechanical-based method for assessing the viability of myocardial tissue, with particular interest for its application in myocardial infarction (MI) diagnosis. This assessment technique quantifies the myocardial contraction forces developed within the ventricular myofibrils in response to the electrophysiological...
Most of the efforts concerning the digital representation of humans (Virtual Humans, or VHs) have been focused on synthesizing geometry for static or animated shapes. The next step is to consider VHs as active semantic entities with features, functionalities, interaction skills, etc. The ontology for VHs we are defining will provide the "semantic layer" required to reconstruct, store, retrieve...
The slice-adaptive histogramming method for improving coarse segmentation of structures from volume data (especially extraction of anatomical structures in the lower torso from computerized tomography data) is introduced. The method uses a series of local histograms to enable a final segmentation that can adapt to slice-to-slice intensity variations.
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