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Malignant and benign clustered microcalcifications: automated feature analysis and classification.
Abstract
PURPOSE: To develop a method for differentiating malignant from benign clustered microcalcifications in which image features are both extracted and analyzed by a computer. MATERIALS AND METHODS: One hundred mammograms from 53 patients who had undergone biopsy for suspicious clustered microcalcifications were analyzed by a computer. Eight computer-extracted features of clustered microcalcifications were merged by an artificial neural network. Human input was limited to initial identification of the microcalcifications. RESULTS: Computer analysis allowed identification of 100% of the patients with breast cancer and 82% of the patients with benign conditions. The accuracy of computer analysis was statistically significantly better than that of five radiologists (P = .03). CONCLUSION: Quantitative features can be extracted and analyzed by a computer to distinguish malignant from benign clustered microcalcifications. This technique may help radiologists reduce the number of false-positive biopsy findings.
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Cited by
Computer-aided diagnosis in medical imaging: historical review, current status and future potential
Doi, K. (2007) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2007.02.002 · Cited by 1,855
Self-citationGiger, M. L., Chan, H., & Boone, J. (2008) · Medical Physics · doi:10.1118/1.3013555 · Cited by 311
Self-citationKohli, A., & Jha, S. (2018) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2017.12.029 · Cited by 114
Metadata
- Authors
- Jiang, Y., Nishikawa, R. M., Wolverton, D. E., Metz, C. E., Giger, M. L., Schmidt, R. A., Vyborny, C. J., & Doi, K.
- Venue
- Radiology
- Published
- 1996-03
- Volume
- 198
- Issue
- 3
- Pages
- 671-678
- ISSN
- 0033-8419 (ISSN-L)
- 1527-1315
- OpenAlex
- W1981103483
- Cited by
- 205
- References
- 0
- FWCI
- 14.90
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Malignant and benign clustered microcalcifications: automated feature analysis and classification. https://app.cochat.ai/papers/10.1148/radiology.198.3.8628853
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- Jiang, Y., Nishikawa, R. M., Wolverton, D. E., Metz, C. E., Giger, M. L., Schmidt, R. A., Vyborny, C. J., & Doi, K. (1996). Malignant and benign clustered microcalcifications: automated feature analysis and classification. Radiology. https://doi.org/10.1148/radiology.198.3.8628853
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