Artificial intelligence (AI) software developer Optellum and imaging software developer Mirada Medical have partnered on deep learning and presented a lung cancer study resulting from their collaboration at RSNA 2017 in Chicago.
Led by Dr. Sarim Ather, PhD, who also presented the study findings at the RSNA meeting, researchers from Oxford University Hospitals in the U.K. assessed CT texture analysis as a tool for lung nodule follow-up. Radiologists often struggle to determine if a lung nodule detected with CT is cancerous, leading to an indeterminate diagnosis that may require up to a two-year follow-up to monitor growth.
The Optellum and Mirada are using AI-based decision-support software to improve patient management and reduce unnecessary follow-up procedures. It uses deep learning and provides an objective risk score of nodule malignancy learned from a database of tens of thousands of CT scans with known diagnoses, allowing clinicians to stratify lung nodule patients earlier, according to the companies.
The software will be featured in the Mirada Medical booth (No. 6520) and the Quantitative Imaging Reading Room (QRR013) at RSNA 2017.















![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&fit=crop&h=112&q=70&w=112)



