Arnav Bhavsar

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Classification of brain fiber tracts is an important problem in brain tractography analysis. We propose a supervised algorithm which learns features for anatomically meaningful fiber clusters, from labeled DTI white matter data. The classification is performed at two levels: a) Grey vs White matter (macro level) and b) White matter clusters (micro level).(More)
Depth map sensed by low-cost active sensors are often limited in resolution, whereas depth information achieved from structure from motion or sparse depth scanning techniques may result in a sparse point cloud. Achieving a high resolution (HR) depth map from a low resolution (LR) depth map or densely reconstructing a sparse non-uniformly sampled depth map(More)
In recent years, the usefulness of 3D shape estimation is being realized in microscopic or close-range imaging, as the 3D information can further be used in various applications. Due to limited depth of field at such small distances, the defocus blur induced in images can provide information about the 3D shape of the object. The task of `shape from defocus'(More)