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|Scopus||Web of Science®||Altmetric|
|Title:||Automated detection of lung nodules in computed tomography images: a review|
|Citation:||Machine Vision and Applications: an international journal, 2012; 23(1):151-163|
|S.L.A. Lee, A.Z. Kouzani and E.J. Hu|
|Abstract:||Lung nodules refer to a range of lung abnormalities the detection of which can facilitate early treatment for lung patients. Lung nodules can be detected by radiologists through examining lung images. Automated detection systems that locate nodules of various sizes within lung images can assist radiologists in their decision making. This paper presents a study of the existing methods on automated lung nodule detection. It introduces a generic structure for lung nodule detection that can be used to represent and describe the existing methods. The structure consists of a number of components including: acquisition, pre-processing, lung segmentation, nodule detection, and false positives reduction. The paper describes the algorithms used to realise each component in different systems. It also provides a comparison of the performance of the existing approaches.|
|Rights:||© Springer-Verlag 2010|
|Appears in Collections:||Aurora harvest|
Environment Institute publications
Mechanical Engineering publications
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