Automatic Detection of Suspicious Lesions in Digital X-ray Mammograms
Abdelali Elmoufidi, Khalid El Fahssi, Said Jai Andaloussi, Abderrahim Sekkaki, Gwenolé Quellec, Mathieu Lamard, Guy Cazuguel · Lecture notes in electrical engineering · 2016
Mammography remains the most effective tool for the early detection of breast cancer, as well as the systems of computer-aided detection/diagnosis (CAD) is typically used as a second opinion by the radiologists. So, the main goal of our method is to introduce a new approach for automatic detecting the suspicious lesions in mammograms (regions of interest) for early diagnosis of breast cancer. This study has two phases: The first one is the preprocessing step and the second one is the detection of Regions of Interest (ROIs). Our method has tested with the well-known Mammography Image Analysis Society (MIAS) database and we’ve used Free-Receiver Operating Characteristics (FROC) to measure methods performance. The obtained experimental results show that our algorithm’s performance has sensitivity of 94.75 % at 0.54 false positive per image.