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…
In plain words
Neuralrad Mammo AI is a free research tool for analyzing mammogram images using deep learning and vision language models. Users upload JPEG or PNG mammogram images, and the tool identifies potential masses and calcifications, then provides radiologist-style analysis with an interactive viewer. Designed for researchers and medical professionals, it explicitly is not FDA-cleared and not for clinical diagnosis—results serve only as secondary opinion for investigation purposes. The tool requires no registration or payment and retains no data.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
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
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