aceReal-time artificial intelligence-based anatomy recognition in single-port transvesical enucleation of the prostate
To evaluate the feasibility and accuracy of an artificial intelligence (AI) model to assist surgeons through automated real-time detection and segmentation of key anatomical structures during robot-assisted single-port transvesical enucleation of the prostate (STEP). This retrospective single-centre study utilised surgical videos from patients undergoing single-port robot-assisted transvesical prostate enucleation performed by a single expert surgeon. Selected frames extracted from these surgical videos were man…
An AI model trained on surgical video frames achieved automated real-time detection and segmentation of bladder neck, adenoma and peripheral zone during robot-assisted prostate enucleation with high Dice scores and >60 fps inference.
Pilot feasibility study was retrospective, single-centre, and based on videos from a single expert surgeon with only 611 annotated frames, limiting generalizability.
Evidence
- Peer-reviewedBJU International2026-08-13
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Truvace Impact Record TRV-2026-0791, v1: “Real-time artificial intelligence-based anatomy recognition in single-port transvesical enucleation of the prostate.” Truvace, 2026-08-16. /record/TRV-2026-0791 (accessed at citation time). sha256 223c0ff270653891…
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