Improved endoscope distortion correction does not necessarily enhance mucosa-classification based medical decision support systems

Author

Gschwandtner, M. ; Hämmerle-Uhl, J. ; Höller, Y. ; Liedlgruber, M. ; Uhl, A. ; Vecsei, A.

Author_Institution

Dept. of Comput. Sci., Univ. of Salzburg, Salzburg, Austria

fYear

2012

fDate

17-19 Sept. 2012

Firstpage

158

Lastpage

163

Abstract

Distortion correction in two variants is applied to endoscopic duodenal imagery aiming at an improvement of automated classification of celiac disease affected mucosa patches. In a set of heterogeneous feature extraction techniques, only geometry and shape related ones are able to benefit from distortion correction, while for others, even a decrease of classification accuracy is observed. Different types of distortion correction do not lead to significantly different behaviour in the observed application scenario.

Keywords

decision support systems; diseases; endoscopes; image classification; medical computing; patient diagnosis; automated classification; celiac disease; endoscope distortion correction; endoscopic duodenal imagery; heterogeneous feature extraction techniques; medical decision support systems; mucosa patches; mucosa-classification; Accuracy; Calibration; Diseases; Endoscopes; Feature extraction; Image edge detection; Nonlinear distortion; endoscope distortion correction; medical decision support systems; mucosa texture classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia Signal Processing (MMSP), 2012 IEEE 14th International Workshop on

Conference_Location

Banff, AB

Print_ISBN

978-1-4673-4570-5

Electronic_ISBN

978-1-4673-4571-2

Type

conf

DOI

10.1109/MMSP.2012.6343433

Filename

6343433