Medical Image Analysis Software
for radiology and research.
SwiftVision AI builds healthcare computer vision for radiology and clinical research teams: tumor detection, image segmentation and analysis pipelines that work with DICOM images.
Healthcare Computer Vision
for medical imaging.
Healthcare computer vision applies AI to medical images such as CT, MRI and X-ray scans to find, measure and classify what clinicians need to see. SwiftVision AI builds these models and pipelines for imaging and research teams.
Medical Imaging Dashboard
for radiology teams.
One study viewer for CT, MRI and X-ray with AI segmentation overlays, confidence scores, model output and a patient queue.
How medical imaging AI works,
in four simple steps.
From DICOM studies in your PACS to AI findings your radiologists can review, with experts making every final call.
Connect your imaging data
DICOM studies are pulled from your PACS or research archive, on-premise or in a private cloud.
AI models analyse each study
Detection, segmentation and classification models find and outline regions of interest, such as tumors, on every scan.
Findings come with confidence
Results appear as overlays, measurements and confidence scores, and can be sent back to PACS and RIS.
Experts review and decide
Radiologists and researchers review AI output in their usual viewer, and every final decision stays with them.
Healthcare AI Use Cases
for imaging and research.
From radiology centers to clinical research labs, medical imaging AI that speeds up image review and keeps analysis consistent.
Radiology Centers
AI triage flags studies with likely critical findings, so radiologists can read them first.
Clinical Research
Reproducible medical image segmentation pipelines for cohort and clinical trial studies.
Imaging Networks
Standardize AI-assisted reading workflows across multi-site radiology reading rooms.
Healthcare AI demos
for medical image analysis.
Brain Tumor MRI Segmentation
Image Enhancement & Object Extraction
Object Detection & Size Measurement
Healthcare AI case studies
with results you can measure.
Radiology center cut triage time by 90%
Problem • Critical findings sat buried in long radiology reading queues.
Result • AI triage now moves studies with likely critical findings to the top of the worklist.
Research lab standardized medical image segmentation
Problem • Manual segmentation varied from reader to reader, which made cohort studies hard to compare.
Result • Reproducible AI segmentation pipelines now run across 12k+ imaging studies.
Imaging network deployed AI across 8 sites
Problem • Each reading room used different AI tools and workflows.
Result • One DICOM-native medical imaging AI workflow now runs in every site.
Medical imaging AI,
your questions answered.
The questions radiology, research and hospital IT teams ask most.
What is healthcare computer vision?
Healthcare computer vision uses AI to read medical images and video, such as MRI, CT and X-ray scans, and find, measure or classify what clinicians and researchers need to see. SwiftVision AI builds these models and pipelines for imaging and research teams.
What can medical image analysis software do?
It can detect and segment tumors and other regions of interest, classify and triage studies, measure structures, and show results as overlays with a confidence score, so experts review the output instead of starting from scratch.
Which imaging modalities do you work with?
Our work covers modalities such as MRI, CT and X-ray, with DICOM-native image ingestion. Other image types, such as dermatology or microscopy images, can be scoped with our team.
Does it integrate with PACS and RIS?
Yes. Studies can be pulled from your PACS and results sent back into PACS and RIS, so radiologists see AI output inside the tools they already use.
Can it run on-premise?
Yes. Models can be deployed on-premise inside your network or in a private cloud, depending on how your organisation handles imaging data.
Is this an FDA-cleared diagnostic device?
Unless a project states otherwise, our imaging models are built for research and workflow support, not as cleared diagnostic devices. Final clinical decisions stay with qualified clinicians. Talk to us about the regulatory path for your intended use.
How much does medical imaging AI cost?
The cost depends on the modalities and tasks you need, how much labelled data exists, and whether the system runs on-premise or in the cloud. If you want a number for your project, book a demo and we will talk through scope and pricing.
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