MIRROR: Multimodal Intelligent Radiology Reasoning and Observation Reporter
A radiologist reading a model's output faces two problems. The model returns a number and no reason, and any system that turns that number into readable prose can quietly add claims the model never made. MIRROR is a research prototype built to separate those failures. It chains a multi-label classifier, a Grad-CAM localizer that turns each positive finding into a named anatomical region, and a report writer that receives the labels, probabilities, and regions but never the image. Because the language layer cannot see pixels, it cannot assert a finding the classifier did not make. We are precis
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 51%Using AI Could Help Patients Understand Radiology Reports - Radiological Society of North America | RSNA →
- PossiblePossibly related (embedding) · 50%Real-time dental image verification with Amazon SageMaker AI at Henry Schein One →
- PossiblePossibly related (embedding) · 48%AI-backed imaging workflow helps generalist radiologists perform like breast specialists - Radiology Business →
- PossiblePossibly related (embedding) · 45%A behind-the-scenes look at Midjourney’s medical scanner leaves many questions unanswered →
- LinkedLinked via arxiv author · 85%Vignesh Nagarajan →
“MIRROR: Multimodal Intelligent Radiology Reasoning and Observation Reporter”
- LinkedLinked via arxiv author · 85%Sriram Venkatapathy →
“MIRROR: Multimodal Intelligent Radiology Reasoning and Observation Reporter”
