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

Myocardial Infarction Detection

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

[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

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

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

[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.

Echo Cardiology Center : "A Comprehensive Tool for Cardiac Echo Reporting" Medical Echo Application “This application is based on the textbook ‘Braunwald’s Heart Disease: A Textbook of Cardiovascular Medicine, 2-Volume Set, 11th Edition.’” This application is developed using Node.js and Bootstrap.

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

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

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

Official implementation of Mitral Valve Segmentation using Robust Nonnegative Matrix Factorization

A spatial feedback attention module (FBA) to enhance unsupervised 3D DLIR

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.

[ASMUS 2023] Synthetic Boost: Leveraging Synthetic Data for Enhanced Vision-Language Segmentation in Echocardiography

A deep learning application to uncover echocardiographic phenotypes

Reconstructing my PhD dissertation