Microcalcification clusters in mammograms are an important early sign of breast cancer. The enhancement of mieroealcifications in mammograms is one of the most important preprocessing techniques for the extraction of ...Microcalcification clusters in mammograms are an important early sign of breast cancer. The enhancement of mieroealcifications in mammograms is one of the most important preprocessing techniques for the extraction of cluster mierocalcifications. In this paper, we present a novel method for the enhancement of microcalcifications. Firstly, the initial microcaleification edges were extracted by using kirsch edge operator, and the diseontinouse edges were linked by employing fi＇aetal teehnique, Then, the continuous closed edges of microcalcifications were filled by using seed filling algorithm. The pixel values of the filled region were replaced by the corresponding pixel values in the original image. Finally, the enhancement of microcalcifications in mammograms was achieved by adding the filled image to the original image. We evaluated the performance of our algorithm by using 50 regions of interesting （ROIs） with microcalcification clusters from DDSM database. The experiment results demonstrate that our CAD system can give better enhancement effect compared with other methods.展开更多
基金National Natural Science Foundation of China grant number: 30971019
文摘Microcalcification clusters in mammograms are an important early sign of breast cancer. The enhancement of mieroealcifications in mammograms is one of the most important preprocessing techniques for the extraction of cluster mierocalcifications. In this paper, we present a novel method for the enhancement of microcalcifications. Firstly, the initial microcaleification edges were extracted by using kirsch edge operator, and the diseontinouse edges were linked by employing fi＇aetal teehnique, Then, the continuous closed edges of microcalcifications were filled by using seed filling algorithm. The pixel values of the filled region were replaced by the corresponding pixel values in the original image. Finally, the enhancement of microcalcifications in mammograms was achieved by adding the filled image to the original image. We evaluated the performance of our algorithm by using 50 regions of interesting （ROIs） with microcalcification clusters from DDSM database. The experiment results demonstrate that our CAD system can give better enhancement effect compared with other methods.
