Extraction of Ruler Markings For Estimating Physical Size of Oral Lesions

  • 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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

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.

Original languageEnglish
Title of host publication2022 26th International Conference on Pattern Recognition, ICPR 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4241-4247
Number of pages7
ISBN (Electronic)9781665490627
DOIs
StatePublished - 2022
Externally publishedYes
Event26th International Conference on Pattern Recognition, ICPR 2022 - Montreal, Canada
Duration: 21 08 202225 08 2022

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2022-August
ISSN (Print)1051-4651

Conference

Conference26th International Conference on Pattern Recognition, ICPR 2022
Country/TerritoryCanada
CityMontreal
Period21/08/2225/08/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • Oral images
  • cross-dataset evaluation
  • deep learning
  • digits detection
  • ruler measurement
  • ruler segmentation

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