no code implementations • 20 Jun 2022 • Babak Haghighi, Warren B. Gefter, Lauren Pantalone, Despina Kontos, Eduardo Mortani Barbosa Jr
Purpose: To utilize high-resolution quantitative CT (QCT) imaging features for prediction of diagnosis and prognosis in fibrosing interstitial lung diseases (ILD).
no code implementations • 11 Jun 2022 • Ramya Muthukrishnan, Angelina Heyler, Keshava Katti, Sarthak Pati, Walter Mankowski, Aprupa Alahari, Michael Sanborn, Emily F. Conant, Christopher Scott, Stacey Winham, Celine Vachon, Pratik Chaudhari, Despina Kontos, Spyridon Bakas
Two U-Nets were separately trained on algorithm-generated labels to perform segmentation of the breast and dense tissue from these images and subsequently calculate breast percent density (PD).
1 code implementation • 26 Feb 2021 • Sarthak Pati, Siddhesh P. Thakur, İbrahim Ethem Hamamcı, Ujjwal Baid, Bhakti Baheti, Megh Bhalerao, Orhun Güley, Sofia Mouchtaris, David Lang, Spyridon Thermos, Karol Gotkowski, Camila González, Caleb Grenko, Alexander Getka, Brandon Edwards, Micah Sheller, Junwen Wu, Deepthi Karkada, Ravi Panchumarthy, Vinayak Ahluwalia, Chunrui Zou, Vishnu Bashyam, Yuemeng Li, Babak Haghighi, Rhea Chitalia, Shahira Abousamra, Tahsin M. Kurc, Aimilia Gastounioti, Sezgin Er, Mark Bergman, Joel H. Saltz, Yong Fan, Prashant Shah, Anirban Mukhopadhyay, Sotirios A. Tsaftaris, Bjoern Menze, Christos Davatzikos, Despina Kontos, Alexandros Karargyris, Renato Umeton, Peter Mattson, Spyridon Bakas
Deep Learning (DL) has the potential to optimize machine learning in both the scientific and clinical communities.
1 code implementation • 13 Nov 2020 • Omid Haji Maghsoudi, Aimilia Gastounioti, Christopher Scott, Lauren Pantalone, Fang-Fang Wu, Eric A. Cohen, Stacey Winham, Emily F. Conant, Celine Vachon, Despina Kontos
Our method has been trained and validated on a multi-ethnic, multi-institutional dataset of 15, 661 images (4, 437 women), and then tested on an independent dataset of 6, 368 digital mammograms (1, 702 women; cases=414) for both PD estimation and discrimination of breast cancer.