3 ms·
Show HN: Free mammogram analysis tool combining deep learning and vision LLM
I've built Neuralrad Mammo AI, a free research tool that combines deep learning object detection with vision language models to analyze mammograms. The goal is to provide researchers and medical professionals with a secondary analysis tool for investigation purposes.
Important Disclaimers:
- NOT FDA 510(k) cleared - this is purely for research investigation
- Not for clinical diagnosis - results should only be used as a secondary opinion
- Completely free - no registration, no payment, no data retention
What it does:
1. Upload a mammogram image (JPEG/PNG)
2. AI identifies potential masses and calcifications
3. Vision LLM provides radiologist-style analysis
4. Interactive viewer with zoom/pan capabilities
You can try it with any mass / calcification mammo images, e.g. by searching Google: mammogram images mass
Key Features:
- Detects and classifies masses (benign/malignant)
- Identifies calcifications (benign/malignant)
- Provides confidence scores and size assessments
- Generates detailed analysis using vision LLM
- No data storage - images processed and discarded
Use Cases:
- Medical research and education
- Second opinion for researchers
- Algorithm comparison studies
- Teaching tool for radiology training
- Academic research validation
The implementation details include:
1. 1st stage object detection using PyTorch retinalnet training DDSM+Internal data set
2. 2nd stage fine tuned Qwen2.5 VL with labeled data + radiology report sets
3. Server is implemented with Flask, Client implemented using SvelteJS
The system is designed specifically for research investigation purposes and to complement (never replace) professional medical judgment. I'm hoping this can be useful for the medical AI research community and welcome feedback on the approach.
Address: http://mammo.neuralrad.com:5300 http://mammo.neuralrad.com:5300
- deleted 1y ago[deleted]
- potato-peeler 1y agoInteresting project. Do you have a write up on how you built this or gh repo?
- coolwulf 1y agoI will write a blog post of details of the implementation. Will post later on HN. Thanks for the interests.
- BrokenCogs 1y agoHow are you hosting it? Heroku?
- coolwulf 1y agoI'm hosting on my own server.
- jph 1y agoExcellent work, thank you. Can you do me a favor and contact me about this? I'm joel@joelparkerhenderson.com and I'm working with public sector health care organizations that are seeking examples of AI for radiographic imaging.
- coolwulf 1y agoI just sent you an email from my personal gmail.
- deleted 1y ago[deleted]
- rvz 1y agoIs this ISO 27001 and HIPPA compliant? It doesn't seem to be open source either.
- coolwulf 1y agoFor research purpose only. And please use anonymized / de-identified data. The server is not keeping any data.
- doctorpangloss 1y agoWhy not fine tune Path Foundation?
- coolwulf 1y agoI have not heard about them.
- hiatus 1y agoYou are encouraging people to upload medical data yet you do not use HTTPS. This just feels irresponsible.
- coolwulf 1y agoWill change it to https as you suggest. Just need to get the ssl certificate.
- notme1234 1y agodang Isn't this a repost of this: https://news.ycombinator.com/item?id=31449147 https://news.ycombinator.com/item?id=31449147 Just added "LLM".
- coolwulf 1y agoIt is the updated version with a newly trained model with more data and added VLLM stage.
- kakoni 1y agoHi! Nice project. Question,"labeled data + radiology report sets", was this something in public domain?