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In this paper, we propose an efficient groupwise morphometric analysis to characterize morphological variations between healthy and pathological states. The proposed framework extends the work of Baloch in which a manifold for each anatomy was constructed by collecting lossless [transformation, residual] descriptors with various transformation parameters, and the optimal set of transformation parameters...
In this paper, the principles of sparse signal representation theory are explored in order to perform facial expressions recognition from frontal views. Motivated by the success such methods have demonstrated in the face recognition problem, we formulate the feature extraction procedure in order to achieve facial expression recognition as an l1 optimization problem. We show that the straightforward...
The reconstruction of complete vascular trees from medical images has many important applications. Although vessel detection has been extensively investigated, little work has been done on how connect the results to reconstruct the full trees. In this paper, we propose a novel theoretical framework for automatic vessel connection, where the automation is achieved by leveraging constraints from the...
We propose a generative model to distinguish normal anatomical variations from abnormal deformations given a group of images with normal and abnormal subjects. We assume that abnormal subjects share common factors which characterize the abnormality. These factors are hard to discover due to large variance of normal anatomical differences. Assuming that the deformation fields are parametrized by their...
In this paper, we propose an efficient technique for creating a visually appealing collage on a mobile platform from a set of input images. The proposed algorithm consists of four main modules, namely image ranking, region of interest (ROI) selection, packing, and blending. Each of the four modules is designed using a greedy and localized approach. The modules are further optimized during implementation...
We present a study on grocery detection using our object detection system, ShelfScanner, which seeks to allow a visually impaired user to shop at a grocery store without additional human assistance. ShelfScanner allows online detection of items on a shopping list, in video streams in which some or all items could appear simultaneously. To deal with the scale of the object detection task, the system...
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