aceArtificial intelligence-based photographic detection of pink esthetic score attributes using a hybrid deep learning segmentation pipeline: a method development study
This study aimed to develop and internally validate a novel anatomy-driven artificial intelligence (AI) system for automated postoperative Pink Esthetic Score (PES) evaluation from intraoral photographs. Unlike most existing AI approaches, which rely on end-to-end prediction, the proposed pipeline derives PES attributes from anatomically grounded measurements. A hybrid analytical pipeline integrating instance segmentation and rule-based measurement was developed. Tooth crown segmentation was performed using Mask…
A hybrid Mask R-CNN and YOLOv11 segmentation pipeline automated postoperative Pink Esthetic Score attribute assessment from intraoral photographs with over 82% accuracy per attribute and 79.3% total-score agreement within one point of experts.
Evidence
- Peer-reviewedScientific Reports2026-08-01
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Truvace Impact Record TRV-2026-0626, v1: “Artificial intelligence-based photographic detection of pink esthetic score attributes using a hybrid deep learning segmentation pipeline: a method development study.” Truvace, 2026-08-03. /record/TRV-2026-0626 (accessed at citation time). sha256 31fc59a58476ce90…
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