A novel mammographic mass detection approach to combining suprevised and unsuprevised detection algorithms
Dae Hoe Kim, Jae Young Choi, Yong Man Ro · 2012
In this paper, we propose the combination of different mass detection algorithms to increase overall mass detection sensitivity for various types of breast masses on mammograms. In particular, supervised and unsupervised mass detection algorithms are effectively combined to maximize complementary effects of both approaches. By combining the aforementioned mass detection algorithms, we can arrive at a combined mass detection approach that makes stronger and accurate detection results. Comparative experiments have been conducted on public mammogram data set. Our results show that the proposed detection system can considerably improve the mass detection sensitivity with relatively small number of false positives, compared to the implementation of using only a single detection solution.