Information Processing in Medical Imaging de Harrison H. Barrett

Information Processing in Medical Imaging: 13th International Conference, IPMI'93, Flagstaff, Arizona, USA, June 14-18, 1993. Proceedings: Lecture Notes in Computer Science, cartea 687

Harrison H. Barrett

Arthur F. Gmitro

This volume contains the proceedings of the thirteenthbiennial International Conference on Information Processingin Medical Imaging (IPMI XIII), held on the campus ofNorthern Arizona University in Flagstaff, Arizona, in June1993. This conference was the latest in a series of meetingswhere new developments in the acquisition, analysis andutilization of medical images are presented, discussed,dissected, and extended. Today IPMI is widely recognized asa preeminent international forum for presentation ofcutting-edge research in medical imaging and imageanalysis.The volume contains the text of the papers presented orallyatIPMI XIII. Over 100 manuscripts were submitted andcritically reviewed, of which 35 were selected forpresentation. In this volume they are arranged into ninecategories: shape description with deformable models,abstractshape description, knowledge-based systems, neuralnetworks, novel imaging methods, tomographic reconstruction,image sequences, statistical pattern recognition, and imagequality.

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Cuprins

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.