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Automatic lung nodule detection from chest CT data using geometrical features: initial results

Chowdhury, Tarik A. and Whelan, Paul F. orcid logoORCID: 0000-0002-2029-1576 (2010) Automatic lung nodule detection from chest CT data using geometrical features: initial results. In: 14th Irish Machine Vision and Image Processing conference (IMVIP 2010), 8-10 Sept 2010, University of Limerick, Ireland.

Abstract
In this paper, a complete system for automatic lung nodule detection from Chest CT data is proposed. The proposed system includes the methods of lung segmentation and nodule detection from CT data. The algorithm for lung segmentation consists ofsurrounding air voxel removal, body fat/tissue identification, trachea detection, and pulmonary vessels segmentation. The nodule detection algorithm comprises of candidate surface generation, geometrical feature generation and classification. The proposed system shows 88.2% sensitivity for nodule >=3mm with 8.91 false positive per dataset.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:computer vision; image analysis; CT data; Lung nodules; Automatic detection
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:18616
Deposited On:14 Aug 2013 10:11 by Mark Sweeney . Last Modified 11 Jan 2019 13:47
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