Texture-based Graph Model of the Lungs for Drug Resistance Detection, Tuberculosis Type Classification, and Severity Scoring: Participation in ImageCLEF 2018 Tuberculosis Task

Yashin Dicente Cid, Henning Müller
2018 Conference and Labs of the Evaluation Forum  
In 2018, ImageCLEF proposed a task using CT (Computed Tomography) scans of patients with tuberculosis (TB). The task was divided into three subtasks: multi-drug resistance detection, TB type classification, and severity scoring. In this work we present a graph model of the lungs capable of characterizing TB patients with different lung problems. The graph contains a fixed number of nodes with weighted edges based on dissimilarity measures between texture descriptors computed in the nodes. This
more » ... odel encodes the texture distribution along the lungs, making it suitable for describing patients with different TB types. The results show the strength of the technique, leading to high results in the three subtasks.
dblp:conf/clef/CidM18 fatcat:zxq72ycbp5h5jkfkyje7lpxylq