abdur75648/Echo-DND

Official implementation of Echo-DND: A Dual Noise Diffusion Model for Robust and Precise Left Ventricle Segmentation in Echocardiography

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Experimental

This project helps cardiologists and medical imaging specialists accurately identify and outline the left ventricle in echocardiogram images. It takes raw ultrasound heart images as input and produces precise, clear segmentations of the left ventricle, even when images are noisy or have low contrast. The primary users are clinicians or researchers who analyze echocardiograms for cardiac diagnostics.

No commits in the last 6 months.

Use this if you need a highly accurate and robust method to segment the left ventricle from noisy or challenging echocardiogram images for cardiac assessment.

Not ideal if you need to segment other heart structures or different types of medical images, as this model is specifically trained and optimized for left ventricle segmentation in echocardiography.

cardiac-diagnostics echocardiography medical-imaging ventricle-segmentation ultrasound-analysis
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 4 / 25
Maturity 7 / 25
Community 14 / 25

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Stars

8

Forks

3

Language

Python

License

Last pushed

Jun 19, 2025

Commits (30d)

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