Transthoracic echocardiography and mortality in sepsis: analysis of the MIMIC-III database

EchoNet-LVH is a deep learning model that quantifies ventricular hypertrophy and predicts etiologies of increased wall thickness and LVH (amyloidosis, HCM, etc).

[ NeurIPS 2022 ] Official Codebase for "ETAB: A Benchmark Suite for Visual Representation Learning in Echocardiography"

Myocardial Infarction Detection

[Communications Medicine] "Efficient deep learning-based automated diagnosis from echocardiography with contrastive self-supervised learning" by Gregory Holste, Evangelos Oikonomou, Bobak Mortazavi, Zhangyang Wang, and Rohan Khera

Official repository for the paper "ProtoASNet: Dynamic Prototypes for Inherently Interpretable and Uncertainty-Aware Aortic Stenosis Classification in Echocardiography" in MICCAI 2023 Conference

PyTorch implementation of the two U-Net-based architectures described in "Deep Learning for Segmentation using an Open Large-Scale Dataset in 2D Echocardiography"

The implementation of CLAS-FV described in "Fully automated multi-heartbeat echocardiography video segmentation and motion tracking".

[European Heart Journal] "Severe aortic stenosis detection by deep learning applied to echocardiography" by Gregory Holste et al.

This repository accompanies our paper Unlocking the Heart Using Adaptive Locked Agnostic Networks and enables replication of the key results.

Official implementation of Mitral Valve Segmentation using Robust Nonnegative Matrix Factorization

Python package for preprocessing OpenSlide image files and their corresponding annotations for use with Machine Learning segmentation models.

Analysis of temporal network architectures for heart phase detection with echocardiogram imaging 🎞🩺🫀

This repository implements a robust deep learning method (LFBNet) for medical image segmentation using a two systems approach. Learning fast and slow strategy for robust medical image analysis.

Synthetic Boost: Leveraging Synthetic Data for Enhanced Vision-Language Segmentation in Echocardiography

A deep learning application to uncover echocardiographic phenotypes

Reconstructing my PhD dissertation

Deep learning segmentation approaches to enforce temporal consistency in echocardiography sequences in collaboration with Physense Research Group from UPF.

List of my published/preprint research.