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Automated mediastinal lymph node detection from CT volumes based on intensity targeted radial structure tensor analysis.
J. Med. Imaging 4:044502 (2017)
This paper presents a local intensity structure analysis based on an intensity targeted radial structure tensor (ITRST) and the blob-like structure enhancement filter based on it (ITRST filter) for the mediastinal lymph node detection algorithm from chest computed tomography (CT) volumes. Although the filter based on radial structure tensor analysis (RST filter) based on conventional RST analysis can be utilized to detect lymph nodes, some lymph nodes adjacent to regions with extremely high or low intensities cannot be detected. Therefore, we propose the ITRST filter, which integrates the prior knowledge on detection target intensity range into the RST filter. Our lymph node detection algorithm consists of two steps: (1) obtaining candidate regions using the ITRST filter and (2) removing false positives (FPs) using the support vector machine classifier. We evaluated lymph node detection performance of the ITRST filter on 47 contrast-enhanced chest CT volumes and compared it with the RST and Hessian filters. The detection rate of the ITRST filter was 84.2% with 9.1 FPs/volume for lymph nodes whose short axis was at least 10 mm, which outperformed the RST and Hessian filters.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
Computer-aided Detection ; Local Intensity Structure Analysis ; Lung Cancer ; Structure Tensor
ISSN (print) / ISBN
2329-4302
e-ISSN
2329-4310
Zeitschrift
Journal of medical imaging
Quellenangaben
Band: 4,
Heft: 4,
Artikelnummer: 044502
Verlag
SPIE
Verlagsort
Bellingham, Wash.
Nichtpatentliteratur
Publikationen
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute for Machine Learning in Biomed Imaging (IML)