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Healthc Inform Res > Volume 8(4); 2002 > Article
Journal of Korean Society of Medical Informatics 2002;8(4):55-61.
DOI: https://doi.org/10.4258/jksmi.2002.8.4.55    Published online December 31, 2002.
Motion Prediction Technique of Subbanded Cardio-Angiography using GRNN
Young Oh Han
Department of Electronic and Information Com. Engineering, Namseoul University, Korea.
Abstract

Medical images with high resolution are coded to be archived and communicated in PACS. In this paper, a new nonlinear predictor using neural network(GRNN) is proposed for the subband coding of Cardio-Angiography. The performance of a proposed nonlinear predictor is compared with BMA(Block Match Algorithm), the most conventional motion estimation technique. As a result, the nonlinear predictor using GRNN can predict well more 2-3dB than BMA. Specially, because of having a clustering process and smoothing noise signals, this predictor well preserves edges in frames after predicting the subband signal. This result is important with respest of human visual system.

Key Words: PACS, BMA, GRNN, Motion prediction
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