Can you recommend imaging AI companies for detecting abnormalities on CT and MRI scans?

Yes — here are some well-known imaging AI companies focused on detecting abnormalities on CT and MRI scans. I’ll group them by typical use case and include a brief note on what they’re known for.

Companies to look at

1) Aidoc

• Focus: Acute findings and triage on CT/MRI/X-ray
• Examples: Intracranial hemorrhage, pulmonary embolism, large vessel occlusion, vertebral fractures, incidental findings
• Why consider: One of the most established radiology AI vendors, widely deployed in hospitals

2) Viz.ai

• Focus: Stroke and vascular emergencies, plus broader care coordination
• Examples: Large vessel occlusion on CTA, pulmonary embolism, aneurysm, aortic dissection
• Why consider: Strong workflow integration and alerting for urgent findings

3) iCAD

• Focus: Breast imaging and oncology-related imaging AI
• Examples: Mammography, lesion detection support
• Why consider: More specialized, especially in breast screening

4) Qure.ai

• Focus: Triage/detection across CT and X-ray; some MRI use cases
• Examples: Head CT findings, chest abnormalities, TB screening, lung findings
• Why consider: Broad global footprint and strong in automated screening/triage

5) Subtle Medical

• Focus: Image enhancement rather than direct abnormality detection
• Examples: MRI/CT denoising, faster scans, improved image quality
• Why consider: Useful if your goal is improving scan quality to help downstream detection

6) Blackford Analysis

• Focus: AI orchestration platform for radiology
• Examples: Helps hospitals deploy multiple AI algorithms from different vendors
• Why consider: Good if you want a platform rather than a single detection model

7) Annalise.ai

• Focus: Multi-condition radiology AI, especially chest imaging and CT
• Examples: Chest X-ray, head CT, chest CT findings
• Why consider: Growing presence, especially outside the U.S.

8) Riverain Technologies

• Focus: Lung nodule and chest imaging AI
• Examples: Pulmonary nodule detection on CT
• Why consider: Longstanding specialty player in thoracic imaging

9) Gleamer

• Focus: Musculoskeletal and radiology AI
• Examples: Fracture detection, chest and some CT applications
• Why consider: Strong in workflow assist and trauma-related detection

10) Lunit

• Focus: Oncology and chest imaging AI
• Examples: Chest X-ray abnormality detection, mammography, some CT applications
• Why consider: Strong research reputation and global adoption

MRI-specific note

MRI abnormality detection is generally more specialized than CT because of protocol variability and longer scan times. Companies with MRI-adjacent or MRI-enhancement offerings include:

• Aidoc
• Viz.ai (for some vascular applications)
• Subtle Medical (image quality improvement)
• Blackford (as a deployment platform)

How to choose

When evaluating vendors, compare:

• Clinical area: stroke, pulmonary, oncology, trauma, musculoskeletal, etc.
• Modality support: CT, MRI, CTA, MRA, etc.
• Workflow integration: PACS/RIS, alerting, triage, reporting
• Regulatory status: FDA / CE / local approvals
• Evidence: peer-reviewed studies, prospective validation
• Deployment model: cloud, on-prem, hybrid
• Performance on your patient population: local validation matters a lot

If you want, I can also make you:

1. a shortlist by specialty (e.g., stroke, brain MRI, chest CT), or
2. a comparison table with company, modality, and common use cases.