Title
Combining Different Reconstruction Kernel Responses As Preprocessing Step For Airway Tree Extraction In Ct Scan
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.
Year
DOI
Venue
2017
10.5220/0006134200890097
PROCEEDINGS OF THE 12TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2017), VOL 4
Keywords
Field
DocType
Airway Tree Segmentation Pipeline, CT Reconstruction Kernels, Data Fusion, CT Chest Scan
Kernel (linear algebra),Computer vision,Pattern recognition,Computer science,Preprocessor,Computed tomography,Artificial intelligence,Airway
Conference
Citations 
PageRank 
References 
1
0.35
0
Authors
4
Name
Order
Citations
PageRank
Samah Bouzidi110.69
Fabien Baldacci210.35
Chokri Ben Amar364382.72
P Desbarats472.34