|Recent talks by members of MIDAG|
|Current Research Areas|
Anatomic Geometry & Deformations and Their Population Statistics (Steve Pizer, 2004)
representations for classes of 3D anatomical structures
Statistical Morphology in Psychiatric Illness
| Image Analysis
and Display Technologies
3D/2D Registration of Curves: Application to Endovascular Intervention
The treatment of vascular disease involving the central nervous system uses state-of-the-art minimally invasive technologies. Using tiny flexible catheters used from within blood vessels, most vessels in the brain and the spinal cord can be accessed to treat disabling diseases without performing open surgery. This project develops a methodology to register a 3D model of the brain vascular tree, obtained with pre-operative image analysis, with 2D angiographic images acquired during the intervention.
variations induced by radiofrequency coil inhomogeneities but also
by the patient severely impede image segmentation by statistical pattern
recognition. The new method calculates a parametric estimate of the
bias field using prior information about tissue probability density
The research in MIDAG focuses on the development of methods of image analysis, visualization, and image processing of medical images and the production of approaches to solving clinical problems that benefit from these methods. In image analysis our methods solve problems of segmentation, registration, shape measurement, and computer aided diagnosis and involve both deformable structural models approaches and statistical pattern recognition approaches.
This project aims
at developing improved image processing methodology for 3D Ultrasound
image data to study lateral cerebral ventricles in the neonatal brain.
Mild enlargement of the fetal lateral ventricles is hypothesized as
a marker of increased risk for poor neurodevelopmental outcome.
This project develops a new structural segmentation technique for blobby 3D structures. Segmentation is driven by object shape rather than image intensity and results in a full shape characterization of the individual objects which helps answering clinical hypothesis about lesion distribution in regard to anatomical and functional brain regions.
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