A segmentation method for lung nodule image sequences based on superpixels and density-based spatial clustering of applications with noise

The fast and accurate segmentation of lung nodule image sequences is the basis of subsequent processing and diagnostic analyses. However, previous research investigating nodule segmentation algorithms cannot entirely segment cavitary nodules, and the segmentation of juxta-vascular nodules is inaccur...

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Vydané v:	PloS one Ročník 12; číslo 9; s. e0184290
Hlavní autori:	Zhang, Wei, Zhang, Xiaolong, Zhao, Juanjuan, Qiang, Yan, Tian, Qi, Tang, Xiaoxian
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Public Library of Science 07.09.2017 Public Library of Science (PLoS)
Predmet:	Accuracy Algorithms Biology and Life Sciences CAT scans Change detection Classification Cluster Analysis Clustering Computed tomography Computer science Databases, Factual Datasets Diagnostic systems Drug dosages Dynamic programming Entropy Health aspects Image enhancement Image processing Image segmentation Imaging, Three-Dimensional International conferences Iterative methods Lung Lung - pathology Lung cancer Lung nodules Medical imaging Medicine and Health Sciences Methods Multivariate analysis Nodules Noise Physical Sciences Preprocessing Radiographic Image Interpretation, Computer-Assisted Research and Analysis Methods Solitary Pulmonary Nodule - pathology Tomography, X-Ray Computed Tumors
ISSN:	1932-6203, 1932-6203
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