ArticleProceedings of the ... IAPR International Conference on Pattern Recognition. International Conference on Pattern Recognition2022
Extraction of Ruler Markings For Estimating Physical Size of Oral Lesions.
Article in Proceedings of the ... IAPR International Conference on Pattern Recognition. International Conference on Pattern Recognition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Weakly Supervised Learning of Oral Cavity Images for Separating Precancer from Cancer.IEEE International Conference on Omni-layer Intelligent Systems : COINS. IEEE International Conference on Omni-layer Intelligent Systems · 2026Article
- RulerNet: Learning perspective-invariant ruler representations for robust image scale estimation.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2026Article
- Trends and Drivers of Head and Neck Cancers in Older Adults Over 30 Years: A Population-Based Modelling Study.Risk management and healthcare policy · 2026Article
- Oral Cancer Detection By Using Tabular Data Synthesis and Classification.Proceedings ... ICDM workshops. IEEE International Conference on Data Mining · 2025Article
- Detecting Oral Cancer Using Tabular Deep Learning.IEEE International Conference on Omni-layer Intelligent Systems : COINS. IEEE International Conference on Omni-layer Intelligent Systems · 2025Article
- Cleaning and Harmonizing Medical Image Data for Reliable AI: Lessons Learned from Longitudinal Oral Cancer Natural History Study Data.Proceedings of SPIE--the International Society for Optical Engineering · 2024Article
Corrections and comments
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Authors and funding
11 authors at 7 institutions in 2 countries.
Funding
Abstract
Small ruler tapes are commonly placed on the surface of the human body as a simple and efficient reference for capturing on images the physical size of a lesion. In this paper, we describe our proposed approach for automatically extracting the measurement information from a ruler in oral cavity images which are taken during oral cancer screening and follow up. The images were taken during a study that aims to investigate the natural history of histologically defined oral cancer precursor lesions and identify epidemiologic factors and molecular markers associated with disease progression. Compared to similar work in the literature proposed for other applications where images are captured with greater consistency and in more controlled situations, we address additional challenges that our application faces in real world use and with analysis of retrospectively collected data. Our approach considers several conditions with respect to ruler style, ruler visibility completeness, and image quality. Further, we provide multiple ways of extracting ruler markings and measurement calculation based on specific conditions. We evaluated the proposed method on two datasets obtained from different sources and examined cross-dataset performance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.