Barrett's Esophagus Analysis Using SURF Features

  • The development of adenocarcinoma in Barrett’s esophagus is difficult to detect by endoscopic surveillance of patients with signs of dysplasia. Computer assisted diagnosis of endoscopic images (CAD) could therefore be most helpful in the demarcation and classification of neoplastic lesions. In this study we tested the feasibility of a CAD method based on Speeded up Robust Feature Detection (SURF). A given database containing 100 images from 39 patients served as benchmark for feature based classification models. Half of the images had previously been diagnosed by five clinical experts as being ”cancerous”, the other half as ”non-cancerous”. Cancerous image regions had been visibly delineated (masked) by the clinicians. SURF features acquired from full images as well as from masked areas were utilized for the supervised training and testing of an SVM classifier. The predictive accuracy of the developed CAD system is illustrated by sensitivity and specificity values. The results based on full image matching where 0.78 (sensitivity) and 0.82 (specificity) were achieved, while the masked region approach generated results of 0.90 and 0.95, respectively.

Export metadata

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:Luis Antonio de SouzaORCiD, Christian Hook, João P. PapaORCiD, Christoph PalmORCiDGND
DOI:https://doi.org/10.1007/978-3-662-54345-0_34
Parent Title (German):Bildverarbeitung für die Medizin 2017; Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 12. bis 14. März 2017 in Heidelberg
Publisher:Springer
Place of publication:Berlin
Document Type:conference proceeding (article)
Language:English
Year of first Publication:2017
Release Date:2019/12/20
GND Keyword:Speiseröhrenkrankheit; Diagnose; Maschinelles Sehen; Automatische Klassifikation
First Page:141
Last Page:146
Institutes:Fakultät Informatik und Mathematik
Regensburg Center of Biomedical Engineering - RCBE
Regensburg Medical Image Computing - ReMIC
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke