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ChartOCR: A Longitudinal OCR System Using a Unified Periodontal Assessment Form
Yunseo Moon1,2, Minh Do Ngoc Luong1,2, Seungjun Chong1,2
1College of Nursing, Seoul National University, Seoul, Republic of Korea.
None:
Periodontitis generates substantial clinical data, yet periodontal and PI charts remain predominantly paper-based, which limits reuse for clinical analysis and decision support. We present ChartOCR, a system that digitizes unified periodontal-plaque forms using template-based alignment, coordinate-based region-of-interest extraction, a fine-tuned TrOCR model, and SHA-256. ChartOCR supports common handwriting conventions and provides an interactive interface with real-time result streaming, in-place correction, and CSV export. We evaluated the system on 30 scanned handwritten charts. Periodontal charts achieved a mean accuracy and mAP of 0.987, while PI charts reached 0.942 accuracy and 0.884 mAP. Most digits performed well, although PPV was lower for higher plaque scores. On a MacBook Pro (M3 Pro), the average processing time per chart was approximately 70 seconds. These results demonstrate that our approach enables accurate, efficient digitization of handwritten dental charts and provides a scalable foundation for periodontal informatics research.
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