Motion Prediction Technique of Subbanded Cardio-Angiography using GRNN.
- Author:
Young Oh HAN
1
Author Information
1. Department of Electronic and Information Com. Engineering, Namseoul University, Korea. youngoh@nsu.ac.kr
- Publication Type:Original Article
- Keywords:
PACS;
BMA;
GRNN;
Motion prediction
- MeSH:
Clinical Coding;
Humans;
Noise;
Statistics as Topic
- From:Journal of Korean Society of Medical Informatics
2002;8(4):55-61
- CountryRepublic of Korea
- Language:Korean
-
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.
