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Atlas-Based Probabilistic Fibroglandular Tissue Segmentation in Breast MRI.

, , and . MICCAI (2), volume 7511 of Lecture Notes in Computer Science, page 437-445. Springer, (2012)

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Distinguishing Lesions from Posterior Acoustic Shadowing in Breast Ultrasound via Non-Linear Dimensionality Reduction., , , and . EMBC, page 3070-3073. IEEE, (2006)Fully-Automated Fibroglandular Tissue Segmentation in Breast MRI., , , , and . Digital Mammography / IWDM, volume 7361 of Lecture Notes in Computer Science, page 244-251. Springer, (2012)Three-dimensional whole breast segmentation in sagittal MR images with dense depth field modeling and localized self-adaptation., , , , , and . Medical Imaging: Image Processing, volume 10133 of SPIE Proceedings, page 1013314. SPIE, (2017)Atlas-Based Probabilistic Fibroglandular Tissue Segmentation in Breast MRI., , and . MICCAI (2), volume 7511 of Lecture Notes in Computer Science, page 437-445. Springer, (2012)Fully automated chest wall line segmentation in breast MRI by using context information., , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 8315 of SPIE Proceedings, page 831507. SPIE, (2012)Interactions of lesion detectability and size across single-slice DBT and 3D DBT., , , , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 10577 of SPIE Proceedings, page 105770X. SPIE, (2018)Fully-automated fibroglandular tissue segmentation and volumetric density estimation in breast MRI by integrating a continuous max-flow model and a likelihood atlas., , , and . Medical Imaging: Computer-Aided Diagnosis, volume 8670 of SPIE Proceedings, page 86701C. SPIE, (2013)Summary of Outcomes from Consecutive Years of Tomosynthesis Screening at an American Academic Institution., , , , , , , , and . Digital Mammography / IWDM, volume 9699 of Lecture Notes in Computer Science, page 20-24. Springer, (2016)Optimized simulation of breast anatomy for virtual clinical trials., , , , and . IWBI, volume 10718 of SPIE Proceedings, page 107181X. SPIE, (2018)Convolutional Neural Network Model Observers Discount Signal-like Anatomical Structures During Search in Virtual Digital Breast Tomosynthesis Phantoms., , , , , and . CoRR, (2024)