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Found 6 papers, 4 papers with code
Echo from noise: synthetic ultrasound image generation using diffusion models for real image segmentation
We propose a novel pipeline for the generation of synthetic ultrasound images via Denoising Diffusion Probabilistic Models (DDPMs) guided by cardiac semantic label maps.
Efficient Pix2Vox++ for 3D Cardiac Reconstruction from 2D echo views
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.
CRISP - Reliable Uncertainty Estimation for Medical Image Segmentation
For this reason, we propose CRISP a ContRastive Image Segmentation for uncertainty Prediction method.
D'ARTAGNAN: Counterfactual Video Generation
Causally-enabled machine learning frameworks could help clinicians to identify the best course of treatments by answering counterfactual questions.
Contrastive Learning for View Classification of Echocardiograms
Analysis of cardiac ultrasound images is commonly performed in routine clinical practice for quantification of cardiac function.
Ultrasound Video Transformers for Cardiac Ejection Fraction Estimation
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.
