Cost-Sensitive ROI Detection Method for Medical Images Based on Cascade Architecture
LI Ning,GUO Qiao-Jin,XIE Jun-Yuan,CHEN Shi-Fu
State Key Laboratory for Novel Software Technology,Nanjing University,Nanjing 210093 Department of Computer Science and Technology,Nanjing University,Nanjing 210093
Abstract：Regions of Interest (ROI) in medical images contain important information and are of great significance to the analysis and diagnosis. A cost-sensitive ROI detection method for medical images based on Cascade architecture is proposed in this paper, which combines the characters of medical images and applies machine learning and image process. This method achieves high sensitivity and efficiency by effectively integrating cost-sensitive classifier method and Cascade architecture. Experimental results on mammograms show that the method is more efficient and less in calculated amount than pixel-based methods, meanwhile avoids the difficulty of detecting masses by using traditional segmentation and filtering techniques with region-based approach.
李宁，郭乔进，谢俊元，陈世福. 基于Cascade结构的代价敏感的医学图像ROI检测方法[J]. 模式识别与人工智能, 2010, 23(2): 228-234.
LI Ning,GUO Qiao-Jin,XIE Jun-Yuan,CHEN Shi-Fu. Cost-Sensitive ROI Detection Method for Medical Images Based on Cascade Architecture. , 2010, 23(2): 228-234.
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