no code implementations • 16 Feb 2024 • Gautam Rajendrakumar Gare, Tom Fox, Beam Chansangavej, Amita Krishnan, Ricardo Luis Rodriguez, Bennett P deBoisblanc, Deva Kannan Ramanan, John Michael Galeotti
Accurate and interpretable diagnostic models are crucial in the safety-critical field of medicine.
no code implementations • 16 Jun 2022 • Gautam Rajendrakumar Gare, Tom Fox, Pete Lowery, Kevin Zamora, Hai V. Tran, Laura Hutchins, David Montgomery, Amita Krishnan, Deva Kannan Ramanan, Ricardo Luis Rodriguez, Bennett P deBoisblanc, John Michael Galeotti
We propose to decouple feature learning from downstream lung ultrasound tasks by introducing an auxiliary pre-task of visual biomarker classification.
no code implementations • 25 Jan 2022 • Gautam Rajendrakumar Gare, Andrew Schoenling, Vipin Philip, Hai V Tran, Bennett P deBoisblanc, Ricardo Luis Rodriguez, John Michael Galeotti
Our segmentation-based models perform better classification when using pretrained segmentation weights, with the dense-label pretrained U-Net performing the best.
no code implementations • 19 Jan 2022 • Gautam Rajendrakumar Gare, Wanwen Chen, Alex Ling Yu Hung, Edward Chen, Hai V. Tran, Tom Fox, Pete Lowery, Kevin Zamora, Bennett P deBoisblanc, Ricardo Luis Rodriguez, John Michael Galeotti
In this paper, we study the significance of the pleura and adipose tissue in lung ultrasound AI analysis.
3 code implementations • 18 Jan 2022 • Gautam Rajendrakumar Gare, Hai V. Tran, Bennett P deBoisblanc, Ricardo Luis Rodriguez, John Michael Galeotti
Due to this, a large amount of lung ultrasound scans have been made available which can be used for AI based diagnosis and analysis.
no code implementations • 27 Aug 2020 • Gautam Rajendrakumar Gare, Jiayuan Li, Rohan Joshi, Mrunal Prashant Vaze, Rishikesh Magar, Michael Yousefpour, Ricardo Luis Rodriguez, John Micheal Galeotti
To the best of our knowledge, this is also the first deep-learning or CNN approach for segmentation that analyses ultrasound raw RF data along with the gray image.