1 code implementation • 2 Aug 2023 • Jeremias Garay, Jocelyn Dunstan, Sergio Uribe, Francisco Sahli Costabal
Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving inverse problems, especially in cases where no complete information about the system is known and scatter measurements are available.
1 code implementation • 22 Nov 2022 • Pablo Arratia López, Hernán Mella, Sergio Uribe, Daniel E. Hurtado, Francisco Sahli Costabal
In this work, we introduce WarpPINN, a physics-informed neural network to perform image registration to obtain local metrics of the heart deformation.
1 code implementation • 18 Nov 2020 • Pablo Pino, Denis Parra, Pablo Messina, Cecilia Besa, Sergio Uribe
Several deep learning architectures have been proposed over the last years to deal with the problem of generating a written report given an imaging exam as input.
no code implementations • 20 Oct 2020 • Pablo Messina, Pablo Pino, Denis Parra, Alvaro Soto, Cecilia Besa, Sergio Uribe, Marcelo andía, Cristian Tejos, Claudia Prieto, Daniel Capurro
Every year physicians face an increasing demand of image-based diagnosis from patients, a problem that can be addressed with recent artificial intelligence methods.