Book chapter
BREAST: A Novel Strategy to Improve the Detection of Breast Cancer
Breast Imaging, pp.438-443
Lecture Notes in Computer Science, Springer International Publishing
2014
DOI: 10.1007/978-3-319-07887-8_61
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.
Details
- Title: Subtitle
- BREAST: A Novel Strategy to Improve the Detection of Breast Cancer
- Creators
- Patrick C Brennan - Faculty of Health Sciences, The University of Sydney, AustraliaPhuong Dung Trieu - Faculty of Health Sciences, The University of Sydney, AustraliaKriscia Tapia - Faculty of Health Sciences, The University of Sydney, AustraliaJohn Ryan - Ziltron, IrelandClaudia Mello-Thoms - Faculty of Health Sciences, The University of Sydney, AustraliaWarwick Lee - BreastScreen New South Wales, Cancer Institute, Australia
- Resource Type
- Book chapter
- Publication Details
- Breast Imaging, pp.438-443
- Publisher
- Springer International Publishing; Cham
- Series
- Lecture Notes in Computer Science
- DOI
- 10.1007/978-3-319-07887-8_61
- eISSN
- 1611-3349
- ISSN
- 0302-9743
- Language
- English
- Date published
- 2014
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology
- Record Identifier
- 9984051898602771
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