Authors:
Samah Bouzidi
1
;
Fabien Baldacci
2
;
Chokri ben Amar
3
and
Pascal Desbarats
2
Affiliations:
1
LaBRI and ReGIM, France
;
2
LaBRI, France
;
3
ReGIM, Tunisia
Keyword(s):
Airway Tree Segmentation Pipeline, CT Reconstruction Kernels, Data Fusion, CT Chest Scan.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Image Enhancement and Restoration
;
Image Formation and Preprocessing
;
Medical Image Applications
;
Segmentation and Grouping
Abstract:
In this paper, we propose a new preprocessing procedure that combines the responses of different Computed Tomography (CT) reconstruction kernels in order to improve the segmentation of the airway tree. These filters are available in all commercial CT scanner. A broad range of preprocessing techniques have been proposed but all of them operate on images reconstructed using a single reconstruction filter. In this work, the new preprocessing approach is based on a fusion of images reconstructed using different reconstruction kernels and can be included as a preprocessing stage in every segmentation pipeline. Our approach has been applied on various CT scans and an experimental comparison study between state of the art of segmentation approaches results performed on processed and unprocessed data has been made. Results show that the fusion process improves segmentation results and removes false positives.