Computer Vision / Medical imaging demo · Independent project
OncoView AI: Explainable Breast Imaging Triage Demo
Dmitri Derevjanko built OncoView AI, an explainable breast imaging triage demo that runs an ensemble classifier and shows Grad-CAM evidence for each prediction.
This is one of 10+ independent public projects by Dmitri Derevjanko. 100+ additional workflows were delivered professionally, mostly under confidentiality, and are not documented here.
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Problem
Medical imaging models are often shown as a probability with no visual evidence, no operating-point choice, and no public way to test behaviour. That is a poor fit for a screening-style discussion where missing a malignant case is costly.
Solution
A research demo where a user picks a curated case or uploads an image, chooses balanced or high-recall mode, and inspects prediction, confidence, and heatmap overlays in one screen.
What Dmitri Derevjanko built
Dmitri trained and packaged a 6-checkpoint EfficientNet ensemble, implemented FastAPI inference for DICOM/PNG/JPG, Grad-CAM overlays, two operating modes, a 20-case gallery, Git LFS for checkpoints, and 24/7 deploy with Nginx, systemd, and GitHub Actions. The GitHub repository documents the code.
Architecture
- Upload or gallery image is normalized and passed through a 6-checkpoint EfficientNet ensemble with optional test-time augmentation.
- Balanced mode vs high-recall mode changes the operating point for more conservative screening behaviour.
- Grad-CAM produces heatmap, overlay, and hotspot cues so the user can see which regions influenced the score.
- Curated demo samples ship with the public service so the full private training set is not required at runtime.
- Checkpoints live on Git LFS; the API runs as a systemd service behind Nginx.
Technologies
- Python
- FastAPI
- PyTorch
- EfficientNet
- Grad-CAM
- OpenCV
- Pydicom
- Git LFS
Result
A live explainable-imaging demo: ensemble inference, two modes, visual evidence, and a public GitHub repo, without shipping the full training dataset.
Limitations
- Research and portfolio demo only. Not a medical device, not CE-marked, not for diagnosis or screening in care.
- Performance on the demo gallery is not a clinical trial result.
- Users must not upload identifiable patient studies to a public demo.
Live demo and source
Live demo: https://oncoview.dmitriderevjanko.com/
GitHub: https://github.com/DmitriDerevjanko/cancer_detector
Portfolio case study: https://dmitriderevjanko.com/projects/oncoview-ai/