Chang Ruey-Feng, Chang-Chien Kuang-Che, Takada Etsuo, Suri Jasjit S, Moon Woo Kyung, Wu Jeffery H K, Cho Nariya, Wang Yi-Fa, Chen Dar-Ren
Dept. of Comput. & Inf. Technol., Nat. Chung Chen Univ., Chiayi, Taiwan.
Conf Proc IEEE Eng Med Biol Soc. 2006;2006:4853-6. doi: 10.1109/IEMBS.2006.260218.
In general, several factors are used for risk estimation in breast cancer detection and early prevention, and one of the important factors in risk of breast cancer is breast density. The mammography is important and effective adjunct in diagnosing the breast cancer. The radiologists would analyze visually the breast density with the BI-RADS lexicon on mammograms. However, this usually causes a large inter-observer variability among the different experienced radiologists. In this paper, we individually adopt three methods, including pixel-based, region-based, and physics-based, to analyze the breast density on mammograms, and the results can offer radiologists a second quantification reading for predicting the risk of breast cancer. The three methods are tested on 208 digital and conventional film mammograms which are scanned from both breasts of 104 patients respectively. The experimental results show that the accuracy of the proposed region-based method, which is more consistent with the radiologists' viewpoint, is 88% more than other two conventional methods.