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Last Update: 2011.04.27
High Resolution 3D Ultrasound Imaging and Quantification of the Murine Heart (Source: NIH).
Tracking and Image Characterization Research (Source: Night Vision, ARL, CACI, Inc.).
Video Data Mining and Target Tracking: A Model Adaptation and Feedback Control Approach (Source: ARO).
Sinkhole Detection and Bridge/Landslide Monitoring for Transportation Infrastructure by Automated Analysis of Interferometric Synthetic Aperture Radar Images (Source: DOT).
Towards the Neurome: Automated Image Analysis for Neuroinformatics (Source: NSF).
This goal of this project is to develop image analysis techniques to detect bridge settlements, landslide occurrences and sinkhole formation using space-borne interferometric synthetic aperture radar images stacks.
This project comprises a body of work that aims at segmentation, morphology generation and statistical morphology comparision towards establishig the neurome.
Constrained Shape Manifolds for Shape Based Recognition
This project defines and analyzes constrained shape manifolds for use in shape based object recognition.
Human Pose Tracking from Monocular Video
This project generates a pose configuration manifold and associated manifold charting techniques for kinematics based human pose tracking from monocular videos.
This project attempts to detect leukocytes in digital video for the purposes of tracking.
This project attempts to more accurately, effectively, and efficiently collect leukocyte behavior in order to develop anti-inflammatory drugs to treat diseases such as Crohn's disease, heart disease, and multiple sclerosis.
This project attempts to derive a novel edge detector, the instantaneous coefficient of variation (ICOV), for speckle edge detection; and based on the ICOV, design and implement speckle reducing anisotropic diffusion (SRAD) algorithm for ultrasounic (radar) imagery.
This project attempts to develop a novel method to calculate the external force for deformable models, including snakes, (a.k.a., active contours), and deformable surfaces.
This project provides a routine to automatically detect and track cells in a 3D space.
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