Detection of H. pylori induced gastric inflammation by diffuse reflectance analysis

Alexandre Krebs (1) , Vania Camilo (2) , Eliette Touati (2) , Yannick Benezeth (1) , Valérie Michel (2) , Grégory Jouvion (3) , Fan Yang (4) , Dominique Lamarque (5) , Franck Marzani (4)

1 Le2i - Laboratoire d'Electronique, d'Informatique et d'Image [EA 7508]
2 Pathogenèse de Helicobacter
3 IP - Institut Pasteur [Paris]
4 Le2i - Laboratoire Electronique, Informatique et Image [UMR6306]
5 BECCOH - Biomarqueurs et essais cliniques en Cancérologie et Onco-Hématologie

Spectral acquisitions contain rich information and thus, are promising modalities for early detection of gastric diseases. In this study, we analyze the diffuse reflectance of the gastric inflammatory lesions induced by the bacterium H. pylori in the mouse stomach. A pipeline has been designed to characterize and classify spectra acquired on mice. The pipeline is based on a band clustering algorithm followed by the computation of meaningful division and subtraction features and by classification with a linear SVM classifier. Currently, the pipeline is able to recognize inflamed stomachs spectra with an accuracy of 98%. These results are promising and the same pipeline could be adapted for the study of gastric pathologies in humans.

Mots clés: Diffuse Reflectance Analysis; Gastric Diseases; Helicobacter pylori; Inflammatory lesions; Supervised Learning

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Traitement du signal et de l'image [eess.SP]

Alexandre Krebs, Vania Camilo, Eliette Touati, Yannick Benezeth, Valérie Michel, et al.. Detection of H. pylori induced gastric inflammation by diffuse reflectance analysis. IEEE International Conference on Bioinformatics and Bioengineering, Oct 2018, Taichung, Taiwan. ⟨hal-01939130⟩