Advanced visualization firm TeraRecon has unveiled its new iNtuition AI Data Extractor designed to automatically transform clinicians' archived and day-forward advanced visualization data into valuable artificial intelligence (AI) research-ready training datasets.
Users can convert iNtuition postprocessed data in the normal course of routine clinical reading workflows into volumetric, high-fidelity labeled datasets. The information can be further optimized by leveraging iNtuition as a clinical-quality data labeler to create and train algorithms.
The iNtuition AI Data Extractor is available as an engine that runs locally or in the cloud as part of the EnvoyAI platform. This offering is the first in a series of EnvoyAI engines TeraRecon plans to introduce to streamline the training, delivery, and application of new AI algorithms.
The company will offer the iNtuition AI Data Extractor free for the first 90 studies, followed by a low per-image extraction fee thereafter.
![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)
