On-the-fly detection of images with gastritis aspects in magnetically guided capsule endoscopy

P. W. Mewes; D. Neumann; A. Lj. Juloski; E. Angelopoulou; J. Hornegger

doi:10.1117/12.878803

8 March 2011 On-the-fly detection of images with gastritis aspects in magnetically guided capsule endoscopy

P. W. Mewes, D. Neumann, A. Lj. Juloski, E. Angelopoulou, J. Hornegger

Proceedings Volume 7963, Medical Imaging 2011: Computer-Aided Diagnosis; 79631I (2011) https://doi.org/10.1117/12.878803
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

Capsule Endoscopy (CE) was introduced in 2000 and has since become an established diagnostic procedure for the small bowel, colon and esophagus. For the CE examination the patient swallows the capsule, which then travels through the gastrointestinal tract under the influence of the peristaltic movements. CE is not indicated for stomach examination, as the capsule movements can not be controlled from the outside and the entire surface of the stomach can not be reliably covered. Magnetically-guided capsule endoscopy (MGCE) was introduced in 2010. For the MGCE procedure the stomach is filled with water and the capsule is navigated from the outside using an external magnetic field. During the examination the operator can control the motion of the capsule in order to obtain a sufficient number of stomach-surface images with diagnostic value. The quality of the examination depends on the skill of the operator and his ability to detect aspects of interest in real time. We present a novel computer-assisted diagnostic-procedure (CADP) algorithm for indicating gastritis pathologies in the stomach during the examination. Our algorithm is based on pre-processing methods and feature vectors that are suitably chosen for the challenges of the MGCE imaging (suspended particles, bubbles, lighting). An image is classified using an ada-boost trained classifier. For the classifier training, a number of possible features were investigated. Statistical evaluation was conducted to identify relevant features with discriminative potential. The proposed algorithm was tested on 12 video sequences stemming from 6 volunteers. A mean detection rate of 91.17% was achieved during leave-one out cross-validation.

Citation Download Citation

P. W. Mewes, D. Neumann, A. Lj. Juloski, E. Angelopoulou, and J. Hornegger "On-the-fly detection of images with gastritis aspects in magnetically guided capsule endoscopy", Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 79631I (8 March 2011); https://doi.org/10.1117/12.878803

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