Radiology data mining and analytics software developer Montage Healthcare Solutions will unveil new features for its Search and Analytics software at the upcoming United Kingdom Radiological Congress (UKRC) in June.
The firm will showcase its Follow-Up QC module, a tracking tool designed to help departments monitor, analyze, and optimize follow-up recommendations made by radiologists, according to the vendor. Using the company's natural language processing technology, the module automatically detects and tracks follow-up recommendations and highlights overdue recommendations, Montage said.
Montage will also showcase improvements to its QC module and enhancements for its Search Analyze analytics algorithm. A new module, QC Analytics, allows users to analyze, filter, and explore the data produced by its companion QC module, Montage said.
The company said it will also present its Sequential Search algorithm, which is designed to support complex queries across multiple imaging encounters.
![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)
