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 language | English |
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Title of host publication | Proceedings - International Symposium on Biomedical Imaging |
Pages | 362-365 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 2013 |
Event | 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013 - San Francisco, CA, United States Duration: Apr 7 2013 → Apr 11 2013 |
Other
Other | 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013 |
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Country/Territory | United States |
City | San Francisco, CA |
Period | 4/7/13 → 4/11/13 |
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