Abstract
Early diagnosis of breast cancer is highly dependent on quality breast imaging and precise image interpretation. The BREAST programme is an innovative strategy for reader performance self-evaluation in breast cancer detection. Using an online system, detailed feedback on reader/image interpretation is given instantly. Our strategy is currently focused on mammograms but has the potential to be available for a wide range of medical imaging modalities. BREAST also serves a solution to researchers requiring large observer numbers by facilitating the involvement of experts wherever they are located. In summary, BREAST improves the efficacy of mammographic cancer detection through a system of reader performance monitoring and enables research studies with a large amount of robust data.
Keywords
- early diagnosis
- mammograms
- reading performance
- reporting assessment
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© 2014 Springer International Publishing Switzerland
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Brennan, P.C., Trieu, P.D., Tapia, K., Ryan, J., Mello-Thoms, C., Lee, W. (2014). BREAST: A Novel Strategy to Improve the Detection of Breast Cancer. In: Fujita, H., Hara, T., Muramatsu, C. (eds) Breast Imaging. IWDM 2014. Lecture Notes in Computer Science, vol 8539. Springer, Cham. https://doi.org/10.1007/978-3-319-07887-8_61
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DOI: https://doi.org/10.1007/978-3-319-07887-8_61
Publisher Name: Springer, Cham
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