no code implementations • 30 Jun 2024 • Peng Huang, Xue Gao, Lihong Huang, Jing Jiao, Xiaokang Li, Yuanyuan Wang, Yi Guo
However, the large distribution difference between medical reports and natural texts, as well as high computational complexity in common stable diffusion limit the authenticity and feasibility of the generated medical images.
no code implementations • 30 Dec 2023 • Jing Jiao, Jin Zhou, Xiaokang Li, Menghua Xia, Yi Huang, Lihong Huang, Na Wang, Xiaofan Zhang, Shichong Zhou, Yuanyuan Wang, Yi Guo
In this paper, we present a universal US foundation model, named USFM, generalized to diverse tasks and organs towards label efficient US image analysis.
1 code implementation • 24 Jun 2022 • Sophia Bano, Alessandro Casella, Francisco Vasconcelos, Abdul Qayyum, Abdesslam Benzinou, Moona Mazher, Fabrice Meriaudeau, Chiara Lena, Ilaria Anita Cintorrino, Gaia Romana De Paolis, Jessica Biagioli, Daria Grechishnikova, Jing Jiao, Bizhe Bai, Yanyan Qiao, Binod Bhattarai, Rebati Raman Gaire, Ronast Subedi, Eduard Vazquez, Szymon Płotka, Aneta Lisowska, Arkadiusz Sitek, George Attilakos, Ruwan Wimalasundera, Anna L David, Dario Paladini, Jan Deprest, Elena De Momi, Leonardo S Mattos, Sara Moccia, Danail Stoyanov
For this challenge, we released a dataset of 2060 images, pixel-annotated for vessels, tool, fetus and background classes, from 18 in-vivo TTTS fetoscopy procedures and 18 short video clips.