Textured graph-based model of the lungs : application on tuberculosis type classification and multi-drug resistance detection

Dicente Cid, Yashin (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis); University of Geneva, Switzerland) ; Batmanghelich, Kayhan (University of Pittsburgh, USA) ; Müller, Henning (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) ; University of Geneva, Switzerland)

Tuberculosis (TB) remains a leading cause of death worldwide. Two main challenges when assessing computed tomography scans of TB patients are detecting multi{drug resistance and di_erentiating TB types. In this article we model the lungs as a graph entity where nodes represent anatomical lung regions and edges encode interactions between them. This graph is able to characterize the texture distribution along the lungs, making it suitable for describing patients with different TB types. In 2017, the ImageCLEF benchmark proposed a task based on computed tomography volumes of patients with TB. This task was divided into two subtasks: multi{drug resistance prediction, and TB type classi_cation. The participation in this task showed the strength of our model, leading to best results in the competition for multi{drug resistance detection (AUC = 0.5825) and good results in the TB type classi_cation (Cohen's Kappa coe_cient = 0.1623).


Keywords:
Faculty:
Economie et Services
School:
HEG-VS
Institute:
Institut Informatique de gestion
Subject(s):
Informatique
Publisher:
Cham, Springer
Date:
2018-08
Cham
Springer
Pagination:
pp. 157-168
Published in:
Experimental IR Meets Multilinguality, Multimodality, and Interaction : 9th International Conference of the CLEF Association, CLEF 2018, Avignon, France, September 10-14, 2018, Proceedings
Series Statement:
Lecture Notes in Computer Science book series, vol. 11018
Author of the book:
Bello, Patrice ; ed. ; Aix-Marseille University Marseille Cedex 20 France
Trabelsi, Chiraz ; ed. ; Virtual University of Tunis, Tunis, Tunisia
Mothe, Josiane ; ed. ; Systèmes d’informations, Big Data et Rec, Institut de Recherche en Informatique de Toulouse Cedex 04 France
Murtagh, Fionn ; ed. ; Department of Computer Science University of Huddersfield Huddersfield United Kingdom
DOI:
ISBN:
978-3-319-98931-0
Appears in Collection:



 Record created 2018-10-22, last modified 2019-03-01

Fulltext:
Download fulltext
PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)