Ms. Sarah D. Verboom Profile

Sarah D. Verboom

at Radboud Univ Medical Ctr

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Author

Publications (4)

Proceedings Article | 3 April 2024 Poster + Paper

Estimating deep learning model uncertainty of breast lesion classification to guide reading strategy in breast cancer screening

Sarah Verboom, Jaap Kroes, Mireille J. Broeders, Ioannis Sechopoulos

Proceedings Volume 12927, 129271Y (2024) https://doi.org/10.1117/12.3006713

KEYWORDS: Artificial intelligence, Breast cancer, Cancer detection, Cancer, Breast, Stochastic processes, Mammography, Systems modeling, Performance modeling, Uncertainty analysis

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Proceedings Article | 29 March 2024 Presentation + Paper

Ordering mammograms for improved mammography screening performance

Jessie J. Gommers, Sarah Verboom, Michael Webster, Craig Abbey, Mireille J. Broeders, Ioannis Sechopoulos

Proceedings Volume 12929, 1292906 (2024) https://doi.org/10.1117/12.3004714

KEYWORDS: Mammography, Breast density, Visualization, Education and training, Breast, Statistical analysis, Cancer detection, Cancer, Breast cancer

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SPIE Journal Paper | 28 December 2023 Open Access

Deep learning-based breast region segmentation in raw and processed digital mammograms: generalization across views and vendors

Sarah D. Verboom, Marco Caballo, Jim Peters, Jessie Gommers, Daan van den Oever, Mireille J. M. Broeders, Jonas Teuwen, Ioannis Sechopoulos

JMI, Vol. 11, Issue 01, 014001, (December 2023) https://doi.org/10.1117/12.10.1117/1.JMI.11.1.014001

KEYWORDS: Image segmentation, Education and training, Muscles, Image processing, Breast, Mammography, Data modeling, Atomic force microscopy, Deep learning, Digital mammography

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Proceedings Article | 4 April 2022 Poster + Paper

Deep learning-based breast tissue segmentation in digital mammography: generalization across views and vendors

Sarah Verboom, Marco Caballo, Mireille J. Broeders, Jonas Teuwen, Ioannis Sechopoulos

Proceedings Volume 12032, 1203236 (2022) https://doi.org/10.1117/12.2611437

KEYWORDS: Image segmentation, Breast, Mammography, Image processing, Digital mammography, Convolutional neural networks

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