A Method of Medical Images Combining Classification Based on Bayesian and Neural Network
Jian Chen · 2008
Medical images classification is a new research hotspot for medical image diagnosis automatically and pattern recognition. Its main tasks: firstly,to extract features,which can describe image contents,from training sample image sets; secondly,to classify the test image sets according to those features; finally,to recognize pathological tissue automatically by the classification results and can ensure a more objective and accurate result of clinic medical diagnosis scientifically. In this paper,some key problems of medical image classification are discussed and analyzed and a medical image combining classification method is proposed on the basis of Bayesian and Neural Network. The experiments results show that our medical image combining classifier can make use of the advantages of each classifier,and it can obtain a good classification results.