1 code implementation • 9 May 2023 • David Stojanovski, Uxio Hermida, Pablo Lamata, Arian Beqiri, Alberto Gomez
We propose a novel pipeline for the generation of synthetic ultrasound images via Denoising Diffusion Probabilistic Models (DDPMs) guided by cardiac semantic label maps.
1 code implementation • 27 Jul 2022 • David Stojanovski, Uxio Hermida, Marica Muffoletto, Pablo Lamata, Arian Beqiri, Alberto Gomez
Accurate geometric quantification of the human heart is a key step in the diagnosis of numerous cardiac diseases, and in the management of cardiac patients.
no code implementations • 15 Jun 2022 • Thierry Judge, Olivier Bernard, Mihaela Porumb, Agis Chartsias, Arian Beqiri, Pierre-Marc Jodoin
For this reason, we propose CRISP a ContRastive Image Segmentation for uncertainty Prediction method.
1 code implementation • 3 Jun 2022 • Hadrien Reynaud, Athanasios Vlontzos, Mischa Dombrowski, Ciarán Lee, Arian Beqiri, Paul Leeson, Bernhard Kainz
Causally-enabled machine learning frameworks could help clinicians to identify the best course of treatments by answering counterfactual questions.
no code implementations • 6 Aug 2021 • Agisilaos Chartsias, Shan Gao, Angela Mumith, Jorge Oliveira, Kanwal Bhatia, Bernhard Kainz, Arian Beqiri
Analysis of cardiac ultrasound images is commonly performed in routine clinical practice for quantification of cardiac function.
1 code implementation • 2 Jul 2021 • Hadrien Reynaud, Athanasios Vlontzos, Benjamin Hou, Arian Beqiri, Paul Leeson, Bernhard Kainz
We achieve an average frame distance of 3. 36 frames for the ES and 7. 17 frames for the ED on videos of arbitrary length.