Information Processing in Medical Imaging

HARRISON H. BARRETT received a BS in physics from Virginia Polytechnic Institute, an MS in Physics from MIT, and a PhD in applied physics from Harvard. Dr. Barrett is a professor in the Optical Sciences Center, the Department of Radiology, and the Program in Applied Mathematics and serves as Director of the Center for Gamma-ray Imaging. The holder of twenty-three U.S. patents, he is the recipient of the IEEE Medical Imaging Scientist Award and a Humboldt Prize.

A feature space for derivatives of deformations.- Non-rigid motion analysis in medical images: a physically based approach.- The use of active shape models for locating structures in medical images.- Parameterized feasible boundaries in gradient vector fields.- Multi-resolution stochastic 3D shape models for image segmentation.- Higher order differential structure of images.- Symbolic description of 3-D structures applied to cerebral vessel tree obtained from MR angiography volume data.- Multiscale Medial analysis of medical images.- Arrangement: A spatial relation comparing part embeddings and its use in medical image comparisons.- Characterizing first and second-order patches using geometry-limited diffusion.- Spatial knowledge representation for visualization of human anatomy and function.- A strategy for automated multimodality image registration incorporating anatomical knowledge and imager characteristics.- Model-based Recognition of anatomical objects from medical images.- A multiscale approach to image segmentation using Kohonen networks.- Segmentation of Magnetic resonance brain images using analog constraint satisfaction neural networks.- Fast, non-linear inversion for Electrical Impedance Tomography.- Inverse methods for Optical Tomography.- Feature-guided acquisition and reconstruction of MR images.- Reconstruction of a three-dimensional volume from a motion-corrupted two-dimensional data set in magnetic resonance imaging.- A framework for incorporating structural prior information into the estimation of medical images.- Bayesian reconstruction for emission tomography via deterministic annealing.- Analytical considerations of photon attenuation and system response function in SPECT reconstruction.- MAP image reconstruction using wavelet decomposition.- Tomographic reconstruction using information-weighted spline smoothing.- A 3-D filtered-backprojection reconstruction algorithm for combined parallel- and cone-beam SPECT data.- Foundations of factor analysis of medical image sequences: A unified approach and some practical implications.- Bayesian identification of a physiological model in dynamic scintigraphic data.- Image registration for the investigation of atherosclerotic plaque movement.- Using statistical pattern recognition techniques to control variable conductance diffusion.- Adaptive noise equalization and image analysis in mammography.- Continuous voxel classification by stochastic relaxation: Theory and application to MR imaging and MR angiography.- Multivariate gaussian pattern classification: Effects of finite sample size and the addition of correlated or noisy features on summary measures of goodness.- Measuring detection and localization performance.- Methods for estimating the efficiency of human and computational observers in ultrasonography.- Gabor function based medical image compression.