Výsledky vyhledávání - "Singh, Sadanand"

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Autor: Taha, Ahmed, Vu, Yen Nhi Truong, Mombourquette, Brent, Matthews, Thomas Paul, Su, Jason, Singh, Sadanand

Medical images come in high resolutions. A high resolution is vital for finding malignant tissues at an early stage. Yet, this resolution presents a challenge in terms of modeling long range dependencies. Shallow transformers eliminate this problem,

Externí odkaz: http://arxiv.org/abs/2208.06066

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Adaptation of a deep learning malignancy model from full-field digital mammography to digital breast tomosynthesis

Autor: Singh, Sadanand, Matthews, Thomas Paul, Shah, Meet, Mombourquette, Brent, Tsue, Trevor, Long, Aaron, Almohsen, Ranya, Pedemonte, Stefano, Su, Jason

Mammography-based screening has helped reduce the breast cancer mortality rate, but has also been associated with potential harms due to low specificity, leading to unnecessary exams or procedures, and low sensitivity. Digital breast tomosynthesis (D

Externí odkaz: http://arxiv.org/abs/2001.08381

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A Hypersensitive Breast Cancer Detector

Autor: Pedemonte, Stefano, Mombourquette, Brent, Goh, Alexis, Tsue, Trevor, Long, Aaron, Singh, Sadanand, Matthews, Thomas Paul, Shah, Meet, Su, Jason

Early detection of breast cancer through screening mammography yields a 20-35% increase in survival rate; however, there are not enough radiologists to serve the growing population of women seeking screening mammography. Although commercial computer

Externí odkaz: http://arxiv.org/abs/2001.08382

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A Multi-site Study of a Breast Density Deep Learning Model for Full-field Digital Mammography Images and Synthetic Mammography Images

Autor: Matthews, Thomas P., Singh, Sadanand, Mombourquette, Brent, Su, Jason, Shah, Meet P., Pedemonte, Stefano, Long, Aaron, Maffit, David, Gurney, Jenny, Hoil, Rodrigo Morales, Ghare, Nikita, Smith, Douglas, Moore, Stephen M., Marks, Susan C., Wahl, Richard L.

Purpose: To develop a Breast Imaging Reporting and Data System (BI-RADS) breast density deep learning (DL) model in a multi-site setting for synthetic two-dimensional mammography (SM) images derived from digital breast tomosynthesis exams using full-

Externí odkaz: http://arxiv.org/abs/2001.08383

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