Image Processing Iit Thesis

The correlation-based enhancement filters we are developing depend on first-order partial derivatives and so are less sensitive to noise compared with Hessian-based filters.Additionally, multiple sets of eigenvalues are used so that a distinction between nodules and vessel junctions becomes possible. Vessel enhancement in volumetric data is a necessary prerequisite in various medical imaging applications.

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Large collections of such complex documents are commonly found in legal and security investigations.

We have developed a test collection of several million documents and a prototype system to ingest it. There are numerous collections of scanned documents.

Research on document imaging is done in conjunction with researchers in the University of Maryland, the university at Buffalo, and the IR group at IIT.

Some of the research on geometric modeling is done in conjunction with researchers in the mechanical engineering department at IIT.

This can then be used to asses conditions, plan interventions, and monitor recovery.

We are developing computational techniques for automated analysis, interpretation, and visualization of brain structure and function in f MRI, MRI and DTI brain imaging data.Image based perceptual user interfaces, multimedia databases and multimedia computing, image based biometrics, document analysis and recognition.Research funding to projects involving the Visual Computing Lab in recent years totaled roughly

We are developing computational techniques for automated analysis, interpretation, and visualization of brain structure and function in f MRI, MRI and DTI brain imaging data.

Image based perceptual user interfaces, multimedia databases and multimedia computing, image based biometrics, document analysis and recognition.

Research funding to projects involving the Visual Computing Lab in recent years totaled roughly $1.5M.

A short description of recent and ongoing activities in the lab is provided below.

Research on medical imaging is done in conjunction with researchers in the radiology department at the university of Chicago and the biomedical engineering department at IIT.

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We are developing computational techniques for automated analysis, interpretation, and visualization of brain structure and function in f MRI, MRI and DTI brain imaging data.Image based perceptual user interfaces, multimedia databases and multimedia computing, image based biometrics, document analysis and recognition.Research funding to projects involving the Visual Computing Lab in recent years totaled roughly $1.5M.A short description of recent and ongoing activities in the lab is provided below.Research on medical imaging is done in conjunction with researchers in the radiology department at the university of Chicago and the biomedical engineering department at IIT.The filters we developed are based on eigenvalue analysis of the structure tensor which is a first order differential quantity and so are less sensitive to noise. We investigate the problem of content-based image retrieval in the context of complex document images.Complex documents typically start out on paper and are then electronically scanned.In general, we target the development and application of image analysis techniques to medical, scientific, industrial, and military problems in which automatic or semi-manual processing of images and volumetric data is required to inspect, recognize, enhance, or complement other sensory information.Applications of image based rendering to augmented and virtualized reality and other synthetic environments.The approach is based on a mixture-parametric probabilistic model whereas the model parameters are optimized by maximizing the incomplete-data log-likelihood function through expectation maximization.The mixture components are selected to have Cauchy distributions.

.5M.A short description of recent and ongoing activities in the lab is provided below.Research on medical imaging is done in conjunction with researchers in the radiology department at the university of Chicago and the biomedical engineering department at IIT.The filters we developed are based on eigenvalue analysis of the structure tensor which is a first order differential quantity and so are less sensitive to noise. We investigate the problem of content-based image retrieval in the context of complex document images.Complex documents typically start out on paper and are then electronically scanned.In general, we target the development and application of image analysis techniques to medical, scientific, industrial, and military problems in which automatic or semi-manual processing of images and volumetric data is required to inspect, recognize, enhance, or complement other sensory information.Applications of image based rendering to augmented and virtualized reality and other synthetic environments.The approach is based on a mixture-parametric probabilistic model whereas the model parameters are optimized by maximizing the incomplete-data log-likelihood function through expectation maximization.The mixture components are selected to have Cauchy distributions.

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