![]() ![]() ![]() Exploiting the sparsity of natural signals has led to advances in several application areas including image compression, denoising, inpainting, compressed sensing, blin Sparse methods have been utilized in several learning problems because of their ability to provide parsimonious, interpretable, and efficient models. Sparse models form an important component in image understanding, since they emulate the activity of neural receptors in the primary visual cortex of the human brain. Image understanding has been playing an increasingly crucial role in several inverse problems and computer vision. Thiagarajan, Jayaraman J Turaga, Pavan Spanias, Andreas Image understanding using sparse representations This report summarizes its features and applications, while illustrating iiV's usefulness to the biomedical imaging community It is highly extensible, platform independent, and web-compatible. iiV is an image display tool with many useful features. We present sample applications to illustrate some of the features and capabilities. It can read multiple standard positron emission tomography (PET) and magnetic resonance imaging (MRI) file formats like ECAT, ECAT7, ANALYZE, NIfTI-1 and DICOM. Feature manipulation becomes easier by having a full set of editing capabilities including the following: undo or redo changes drag, copy, delete and paste objects and save objects with their features to a file for future editing. iiV displays 3-D images as 2-dimensional (2-D) slices with each slice being an independent object with independent features such as location, zoom, colors, labels, etc. It is written in Java so it is extensible, is platform independent, and can display images within web pages. This tool was programmed to solve basic problems in 3-D data visualization. iiV, an interactive software program for displaying 3-D brain images, is described. Many tools address this problem however, they often fail to address specific needs and flexibility, such as the ability to work with different data formats, to control how and what data are displayed, to interact with values, and to undo mistakes. Visualizing 3-dimensional (3-D) datasets is an important part of modern neuroimaging research. Lee, Joel T Munch, Kristin R Carlis, John V Pardo, José V International Nuclear Information System (INIS) ![]()
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