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Mammography Reading with Computer-Aided Detection (CAD): Performance of Different Readers.

, , , , , , , , , , , , , , , , , and . Digital Mammography / IWDM, volume 4046 of Lecture Notes in Computer Science, page 97-104. Springer, (2006)

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Detecting the Central Mass of a Spiculated Lesion Using Scale-Orientation Signatures., , and . Digital Mammography / IWDM, volume 13 of Computational Imaging and Vision, page 63-70. Springer, (1998)Prompting in Mammography: How Good Must Prompt Generators Be?, , , , , and . Digital Mammography / IWDM, volume 13 of Computational Imaging and Vision, page 347-354. Springer, (1998)Reader performance in visual assessment of breast density using visual analogue scales: are some readers more predictive of breast cancer?, , , , , , , , , and 4 other author(s). Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 10577 of SPIE Proceedings, page 105770W. SPIE, (2018)Texture-Based Breast Cancer Prediction in Full-Field Digital Mammograms Using the Dual-Tree Complex Wavelet Transform and Random Forest Classification., , , and . Digital Mammography / IWDM, volume 8539 of Lecture Notes in Computer Science, page 209-216. Springer, (2014)Statistical Appearance Models of Mammographic Masses., , , , and . Digital Mammography / IWDM, volume 5116 of Lecture Notes in Computer Science, page 401-408. Springer, (2008)Comparison of Microcalcification Detection Rates and Recall Rates in Digital and Analogue Mammography., , , , , , and . Digital Mammography / IWDM, volume 6136 of Lecture Notes in Computer Science, page 513-517. Springer, (2010)Visual Assessment of Density in Digital Mammograms., , , , , , and . Digital Mammography / IWDM, volume 6136 of Lecture Notes in Computer Science, page 414-420. Springer, (2010)Is there a safety-net effect with computer-aided detection (CAD)?, , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 10952 of SPIE Proceedings, page 109520J. SPIE, (2019)Classification of Breast Tissue by Texture Analysis., and . BMVC, page 1-8. BMVA Press, (1991)Using a convolutional neural network to predict readers' estimates of mammographic density for breast cancer risk assessment., , , , , , , , and . IWBI, volume 10718 of SPIE Proceedings, page 107180D. SPIE, (2018)