Hybrid patch-based and image-wide classification of confocal laser endomicroscopy images in Barrett's esophagus surveillance

E. Veronese, E. Grisan, G. Diamantis, G. Battaglia, C. Crosta, C. Trovato

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Barrett's esophagus (BE) is a premalignant condition characterized by the replacement of normal squamous esophageal epithelium by metaplastic intestinal epithelium containing goblet cells. To be diagnosed and monitored, BE requires a thorough observation of epithelial macro- and microscopic changes. Confocal laser endomicroscopy (CLE) has recently revealed to be a useful technique for in vivo virtual histology for BE surveillance. We present a computer-based method for the automatic classification of gastric metaplasia (GM), intestinal metaplasia (IM) and neoplasia (NPL) on the basis of appearance features of confocal images. Comparing the automatic results with the histological gold standard, the proposed method classifies IM, GM, and NPL confocal images with accuracy comparable to human observer. Moreover, it increases the sensitivity and the specificity of CLE examinations, thus decreasing the number of biopsies needed for BE and neoplasia diagnosis.

Original languageEnglish
Title of host publicationProceedings - International Symposium on Biomedical Imaging
Pages362-365
Number of pages4
DOIs
Publication statusPublished - 2013
Event2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013 - San Francisco, CA, United States
Duration: Apr 7 2013Apr 11 2013

Other

Other2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013
Country/TerritoryUnited States
CitySan Francisco, CA
Period4/7/134/11/13

Keywords

  • adenocarcinoma
  • Barrett's esophagus
  • classification
  • confocal endomicroscopy
  • fractal dimension
  • local binary pattern
  • SVM

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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