Automatic extraction of abnormal regions from lung images
Contribuinte(s) |
[Unknown] |
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Data(s) |
01/01/2009
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Resumo |
A system that could automatically extract abnormal lung regions may assist expert radiologists in verifying lung tissue abnormalities. This paper presents an automated lung nodule detection system consisting of five components: acquisition, pre-processing, background removal, detection, and false positives reduction. The system employs a combination of an ensemble classification and clustering methods. The performance of the developed system is compared against some existing counterparts. Based 011 the experimental results, the proposed system achieved a sensitivity of 100% and a false-positives/slice of 0.67 for 30 tested CT images.<br /> |
Identificador | |
Idioma(s) |
eng |
Publicador |
ISBB |
Relação |
http://dro.deakin.edu.au/eserv/DU:30029211/kouzani-ISBB-2009.pdf http://dro.deakin.edu.au/eserv/DU:30029211/kouzani-automaticextraction-2009.pdf http://isbb2009.wmah.org/ |
Direitos |
2009, ISBB |
Tipo |
Conference Paper |