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Jack Lancaster, Ph.D.
Title:
 Professor of Radiology

Director, Biomedical Image Analysis Division
Location:
 Radiology, Research Imaging Center
E-Mail:
 jlancaster@uthscsa.edu
Mailing Address:
Research Imaging Center
UTHSCSA
7703 Floyd Curl Drive
San Antonio, TX 78229
USA
Publications
Diagnostic Imaging II - Course Information.
My research interest focus on the extraction of information from medical images using the fundamental steps of image processing. I work with programmers and researchers to develop software not available commercially to enable the exploration of new biological and medical research questions using tomographic images (MRI, CT, PET, and SPECT). Medical imaging provides methods for macroscopic measurements of numerous parameters of interest including blood flow, diffusion coefficients, T1, T2, proton density, electrical activity, just to mention a few. The in vivo measurements associated with imaging research are bounded to a spatial resolution of about 1mm, a temporal resolution ranging from 1 msec to minutes, and contrast resolutions as low as 5%. However, special techniques can often be employed to extend these limits.

Current externally funded projects include the development of a probabilistic atlas for the human brain (NIH/NIMH), the human brain database BrainMap (NLM), Aiming theory and robotic positioning of transcranial magnetic stumulators for the brain (NIH/NIMH), and a collaboration for the analysis of MRI parametric images for subjects with 18q- Syndrome (NIH). We’ve established a large database of findings from functional brain imaging studies and provide access to this data using the WWW (http://ric.uthscsa.edu/services).

A number of new projects are underway including development of multifeature segmentation with fuzzy classifiers, high speed calculation of MRI parametric images (T1, T2, and proton density), and high-speed 3-D deformation of brain images to match a standard brain atlas. I supervise Ph.D. students in the Radiological Sciences graduate program that are seeking to discover new methods to measure and model biological systems.
Projects

None currently available