DDAD and DDAD-ASR

DDAD
33
Emerging
DDAD-ASR
31
Emerging
Maintenance 2/25
Adoption 8/25
Maturity 16/25
Community 7/25
Maintenance 2/25
Adoption 8/25
Maturity 16/25
Community 5/25
Stars: 54
Forks: 3
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stars: 57
Forks: 2
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About DDAD

caiyu6666/DDAD

[MICCAI 2022] Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays

This project helps radiologists and medical researchers automatically detect abnormalities in chest X-ray images. It takes standard chest X-rays as input and identifies regions that deviate from normal patterns, indicating potential anomalies. This is designed for clinical researchers and practitioners working with medical imaging to improve diagnostic workflows.

radiology chest-x-ray medical-imaging anomaly-detection diagnostic-support

About DDAD-ASR

caiyu6666/DDAD-ASR

[MedIA 2023] Dual-distribution discrepancy with self-supervised refinement for anomaly detection in medical images

This project helps medical professionals like radiologists or diagnostic technicians identify abnormalities in medical images. It takes standard medical image scans (like X-rays or MRIs) as input and highlights regions that deviate from normal patterns, helping pinpoint potential issues. This tool is designed for those who review a large volume of medical images and need assistance in detecting subtle or rare anomalies.

medical imaging radiology diagnostic assistance anomaly detection medical research

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