Disclaimer: Developers are responsible for making any necessary modifications, validating model performance in the final product, and obtaining any applicable regulatory marketing authorizations before commercialization. HOPPR provides tools and component-level documentation to support regulatory preparation and alignment.
HOPPR® MC Chest Radiography
- Modality: Chest X-ray (frontal PA/AP views)
- Anatomy: Chest – Lungs, heart, pleura, mediastinum, ribs, chest wall
- Model Type: Vision Transformer (ViT) Foundation Model
- Task: Classification fine-tuning with model score output. Internal validation on 24 findings, range 0.77–0.99 AUC.
- Availability: Fine-tuning and inference via the HOPPR® AI Foundry and/or Forward Deployed Services
Foundation Model
Supports binary classification fine-tuning with model score output
HOPPR® MC Chest Radiography
- Modality: Chest X-ray (frontal PA/AP, lateral)
- Anatomy: Chest – Lungs, heart, pleura, mediastinum, ribs, chest wall, and devices (pacemaker, tubes)
- Model Type: VLM – Vit encoder + Q-Former + modernBERTdecoder
- Description: Generates descriptive, structured textual language outputs derived from chest radiography representations for research, development, and evaluation workflows.
- Availability: Gain model access through HOPPR Forward Deployed Services and our Foundry API to run inference and test outputs against your data. Work with FDS to make targeted modifications scoped to your use cases and requirements.
HOPPR® EB 2D Mammography
- Modality: 2D Mammography (FFDM and/or 2D synthetic | CC and MLO views)
- Anatomy: Breast (bilateral; left and right)
- Model Type: Vision Transformer (ViT) Foundation Model with LoRA adapters
- Task: Classification (cancer, density, pacemaker) Internal validation: ROC-AUC 0.90 (cancer), 0.94 (density), 0.99 (pacemaker). Supports laterality labeling and includes 5,400 pathology-proven studies.
- Availability: Fine-tuning and inference via the HOPPR® AI Foundry and/or Forward Deployed Services
Foundation Model
Supports binary classification including: cancer detection, density assessment, and pacemaker identification
HOPPR® EB 2D Mammography
- Modality: 2D digital mammography (FFDM and synthetic 2D from DBT)
- Anatomy: Breast (bilateral; left and right laterality)
- Model Type: 2B-parameter Vision-Language Model (VLM)
- Description: Generates descriptive, structured textual language outputs derived from 2D mammography representations for research, development, and evaluation workflows.
- Availability: Gain model access through HOPPR Forward Deployed Services and our Foundry API to run inference and test outputs against your data. Work with FDS to make targeted modifications scoped to your use cases and requirements.
Available for Inference via the Foundry
Upon Request (Fine-tune with FDS)
CheXagent
2-3b srrg impression: Multimodal VLM
- Modality: Chest X-ray (frontal AP/PA Lateral Optional)
- Anatomy: Chest – lungs, heart, pleura, mediastinum, ribs, chest walls
- Availability: Available for inference via AI Foundry
Findings Card Impressions Card
MedGemma 4B (Google)
Vision-language model
- Modality: Chest X-ray, CT, MRI, histopathology, fundus, dermatology
- Anatomy: Multi-organ, general medical imaging
- Availability: Available for inference via AI Foundry
MedImageInsights (Microsoft)
Vision-language embedding model
- Modality: X-ray, CT, MRI, Mammo, ultrasound, OCT, histopathology, fundus, dermatology
- Anatomy: multi-organ, general medical imaging
- Availability: Available for inference via AI Foundry
NVIDIA NV Reason
CXR 3B: parameter VLM
- Modality: Chest X-ray
- Anatomy: Chest – lungs, heart pleura, mediastinum, ribs, chest wall
- Availability: Available for inference via AI Foundry
NVIDIA NV Generate
CT: 3D latent diffusion model
- Modality: CT : full body up to 127 anatomical classes
- Anatomy: Full body (up to 127 anatomical classes)
- Availability: Available for inference via AI Foundry
NVIDIA NV Generate
MR: 3D latent diffusion model
- Modality: MRI T1, T2, FLAIR, SWI
- Anatomy: Brain, abdomen, cardiovascular, and respiratory
- Availability: Available for inference via AI Foundry
RadFM
Multimodal VLM
- Modality: 2D/3D radiology: X-ray, CT, MRI, and others
- Anatomy: Brain, head/neck, thorax, spine, abdomen, pelvis, upper and lower limbs
- Availability: Available for inference via AI Foundry
Disclaimer: Developers are responsible for making any necessary modifications, validating model performance in the final product, and obtaining any applicable regulatory marketing authorizations before commercialization. HOPPR provides tools and component-level documentation to support regulatory preparation and alignment.
Documentation on third-party models is available on their respective websites.
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The HOPPR® AI Foundry strips away technical complexity, empowering your team to build compliant medical imaging solutions with speed and confidence.