Abstract
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.
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Elmoufidi, A. et al. (2017). Automatic Detection of Suspicious Lesions in Digital X-ray Mammograms. In: El-Azouzi, R., Menasche, D.S., Sabir, E., De Pellegrini, F., Benjillali, M. (eds) Advances in Ubiquitous Networking 2. UNet 2016. Lecture Notes in Electrical Engineering, vol 397. Springer, Singapore. https://doi.org/10.1007/978-981-10-1627-1_29
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DOI: https://doi.org/10.1007/978-981-10-1627-1_29
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