Zhiyun Xue, Kelly Yu, Paul Pearlman, Tseng-Cheng Chen, Chun-Hung Hua, Chung Jan Kang, Chih-Yen Chien, Ming-Hsui Tsai, Cheng-Ping Wang, Anil Chaturvedi, Sameer Antani
{"title":"Extraction of Ruler Markings For Estimating Physical Size of Oral Lesions.","authors":"Zhiyun Xue, Kelly Yu, Paul Pearlman, Tseng-Cheng Chen, Chun-Hung Hua, Chung Jan Kang, Chih-Yen Chien, Ming-Hsui Tsai, Cheng-Ping Wang, Anil Chaturvedi, Sameer Antani","doi":"10.1109/icpr56361.2022.9956251","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":74516,"journal":{"name":"Proceedings of the ... IAPR International Conference on Pattern Recognition. International Conference on Pattern Recognition","volume":"2022 ","pages":"4241-4247"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9728633/pdf/nihms-1840606.pdf","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... IAPR International Conference on Pattern Recognition. International Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icpr56361.2022.9956251","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
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.