Aiforia Technologies has launched Velocity, its software designed to allow medical and scientific experts to speed up and simplify image analysis and produce higher-quality results.
Existing and future customers on the Aiforia platform can reportedly use the following for research purposes:
- Annotation Assistant reduces artificial intelligence (AI) model creation time by reviewing images and searching for areas that can provide good training data.
- Image Match combines tissue registration and overlay with AI model analysis and advanced spatial metrics in an automated way. Results from any analysis, such as object identification or segmentation, can be layered and viewed in parallel or superimposed.
- Integrated AI model validation gives end users an interface to define validation sets and to invite colleagues or consultants to provide scoring or diagnosis according to intended use criteria. The validation tool then provides a human versus AI comparison at the pixel level.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
