A YOLOv8-based object detection model for identifying suspected stenosis regions in coronary angiography frames. This model is the AI core of Atrio, a clinical workflow platform that helps cardiologists review angiography studies faster and with less cognitive load.
The model takes individual frames extracted from DICOM cine sequences and outputs bounding boxes with confidence scores around suspected stenosis regions. It is designed to operate within a human-in-the-loop workflow — a cardiologist reviews and approves every flagged finding before any action is taken.
Intended Use
Primary Use
Assistive frame-level stenosis flagging in coronary angiography studies
Used within the Atrio platform as part of a supervised, human-in-the-loop review workflow
Surfaces high-priority frames for cardiologist review, reducing manual scrubbing through hundreds of cine frames
All AI-flagged findings require explicit cardiologist approval before being accepted
Out-of-Scope Use
Not intended for autonomous clinical diagnosis of any kind
Not validated for imaging modalities outside of coronary angiography
Not a replacement for cardiologist review or clinical judgment
Not intended for pediatric cardiac imaging or non-cardiac vascular imaging
Not suitable for use as a sole basis for treatment decisions
Model Details
Property
Details
Model Type
Object Detection
Architecture
YOLOv8
Input
Angiography frames (JPEG/PNG extracted from DICOM cine sequences)
Uniform frame sampling from cine sequences to reduce redundancy
Augmentation
Horizontal flip
Brightness and contrast jitter
Mosaic augmentation (YOLOv8 default)
Random scaling and translation
Training Configuration
Parameter
Value
Epochs
100
Image Size
640
Optimizer
AdamW
Batch Size
16
Confidence Threshold
0.25
IoU Threshold
0.45
Hardware
GPU (CUDA)
Evaluation
Metrics reported on the internal validation split. External prospective validation is ongoing.
Metric
Value
mAP50
0.72
mAP50-95
0.48
Precision
0.74
Recall
0.69
These numbers reflect performance on the internal held-out validation set and should not be interpreted as clinically validated performance figures. Independent external validation has not yet been completed.
Limitations and Bias
Model performance may vary across different angiography equipment, imaging protocols, and contrast injection techniques
Trained on a limited dataset that may not be representative of all patient populations, demographics, or disease presentations
Detection confidence is reduced in heavily calcified vessels, overlapping artery segments, and low-contrast frames
The model has not been tested on data from all major angiography system manufacturers
Foreshortening and non-standard projection angles may reduce detection accuracy
Should not be used as a sole or primary basis for any clinical decision
External prospective validation has not yet been completed
Clinical Disclaimer
This model is a research and assistive tool developed as part of the Atrio platform.
It is not FDA-cleared, CE-marked, or approved by any regulatory body for clinical use
It is not intended for standalone clinical deployment
All model outputs must be reviewed and approved by a qualified cardiologist before being acted upon
The Atrio platform enforces a human-in-the-loop approval step — no AI finding is accepted without explicit doctor confirmation
Clinical deployment of this model in any setting requires independent validation and appropriate regulatory clearance
Model Files
File
Description
best.pt
Trained YOLOv8 model weights (best checkpoint)
data.yaml
Dataset class configuration file
README.md
Model card
About Atrio
Atrio is an AI-assisted clinical workflow platform for cardiologists. It transforms raw DICOM angiography cine images into prioritized findings, visual evidence, and structured reports — while keeping the doctor fully in control at every step.
This model powers the core detection pipeline within Atrio. It is one component of a larger system that includes a findings inbox, visual evidence panel, voice input during procedures, risk stratification, and automated report generation.
Atrio helps cardiologists go from raw angiography scans to final reports in minutes instead of hours — without changing how they work.
This model is intended for research and assistive use only. Clinical deployment requires independent validation, institutional review, and applicable regulatory approvals. The authors make no warranties regarding the clinical accuracy or safety of this model.
