Dynamic Data-Driven System for Laser Treatment of Cancer is to develop a dynamic data-driven planning and control system for laser treatment of cancer. It includes 1) development of a general mathematical framework; 2) dynamic calibration, verification, and validation processes; 3) design of effective thermo-therapeutic protocols using model predictions.

Spinal Cord/Neurology studies the cavitation in the injured portion of the cord. Reconstruction techniques are used to model the spinal cord, the lesion, and the cavitations in the lesion.

Joint Simulation. We are developing modeling and physical simulation tools for human joints reconstructed from the CT, MRI, and photograph imaging data sets of the visible human.

Visible Human. The availability of the Visible Human Data provides a unique opportunity and challenge for visualization of extremely large datasets. We are using the data for fast isosurfacing and joint modeling and simulation.

Spinal Cord Regeneration. SESCRC(Selelective Electroactive Spinal Cord Regeneration Conduit) isolated targets are imaged and integrated with electronics into 3D engineered tissues and conduits.

Heart Modeling. Constructing an accurate patient-specific heart model is important for the development of customized cardiovascular surgical procedures.

Radiation Therapy. We explore the image enhancement for prostate and rectum in CT images. The asymmetric filter can be applied for the image enhancement. In addtion, we endeavor to enhance the boundary of the prostate.

Pulmonary Embolus Detection. We develope an automatic pulmonary embolus detection algorithm. To detect pulmonary embolism, several algorithms are combined such as blood vessel classification, boundary detection, quantification, and tracking algorithms.

Image-to-Modeling We develop a unified modeling paradigm that starts with an imaging data and builds a geometric model of the biological entity under investigation for this to be used in further analysis and simulation.