Intelligent Data Extraction System for RNFL Examination Reports

Chunjun Hua, Yiqiao Shi, Menghan Hu*, Yue Wu

*Corresponding author for this work

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

1 Scopus citations

Abstract

Glaucoma is the collective term for a group of diseases that cause damage to the optic nerve. Retina nerve fiber layer (RNFL) thickness is an indicative reference for evaluating the progression of glaucoma. In this demo paper, we proposed an intelligent data extraction system for RNFL examination report, which can extract the RNFL thickness data from the report photo. The system consists of two procedures viz. target area segmentation and structure data extraction. This system can reduce the amount of data that needs to be entered manually, thus reducing the manual workload in electronic health records (EHRs) system. The demo video of the proposed system is available at: https://doi.org/10.6084/m9.figshare.20098865.v1.

Original languageEnglish
Title of host publicationArtificial Intelligence - Second CAAI International Conference, CICAI 2022, Revised Selected Papers
EditorsLu Fang, Daniel Povey, Guangtao Zhai, Tao Mei, Ruiping Wang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages537-542
Number of pages6
ISBN (Print)9783031205026
DOIs
StatePublished - 2022
Event2nd CAAI International Conference on Artificial Intelligence, CICAI 2022 - Beijing, China
Duration: 27 Aug 202228 Aug 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13606 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd CAAI International Conference on Artificial Intelligence, CICAI 2022
Country/TerritoryChina
CityBeijing
Period27/08/2228/08/22

Keywords

  • Computer vision
  • Electronic health records
  • Glaucoma
  • Image processing

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