1. Artificial intelligence assisted operative anatomy recognition in endoscopic pituitary surgery
- Author
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Danyal Z. Khan, Alexandra Valetopoulou, Adrito Das, John G. Hanrahan, Simon C. Williams, Sophia Bano, Anouk Borg, Neil L. Dorward, Santiago Barbarisi, Lucy Culshaw, Karen Kerr, Imanol Luengo, Danail Stoyanov, and Hani J. Marcus
- Subjects
Computer applications to medicine. Medical informatics ,R858-859.7 - Abstract
Abstract Pituitary tumours are surrounded by critical neurovascular structures and identification of these intra-operatively can be challenging. We have previously developed an AI model capable of sellar anatomy segmentation. This study aims to apply this model, and explore the impact of AI-assistance on clinician anatomy recognition. Participants were tasked with labelling the sella on six images, initially without assistance, then augmented by AI. Mean DICE scores and the proportion of annotations encompassing the centroid of the sella were calculated. Six medical students, six junior trainees, six intermediate trainees and six experts were recruited. There was an overall improvement in sella recognition from a DICE of score 70.7% without AI assistance to 77.5% with AI assistance (+6.7; p
- Published
- 2024
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