Image‐ versus histogram‐based considerations in semantic segmentation of pulmonary hyperpolarized gas images

Purpose To characterize the differences between histogram‐based and image‐based algorithms for segmentation of hyperpolarized gas lung images. Methods Four previously published histogram‐based segmentation algorithms (ie, linear binning, hierarchical k‐means, fuzzy spatial c‐means, and a Gaussian mi...

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Veröffentlicht in:	Magnetic resonance in medicine Jg. 86; H. 5; S. 2822 - 2836
Hauptverfasser:	Tustison, Nicholas J., Altes, Talissa A., Qing, Kun, He, Mu, Miller, G. Wilson, Avants, Brian B., Shim, Yun M., Gee, James C., Mugler, John P., Mata, Jaime F.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Wiley Subscription Services, Inc 01.11.2021
Schlagworte:	Advanced Normalization Tools Algorithms Artificial neural networks Computer applications convolutional neural network Deep learning Domains Ecosystem Fields (mathematics) functional lung imaging Histograms Humans Image processing Image Processing, Computer-Assisted Image segmentation Lung - diagnostic imaging Lungs Machine learning Magnetic Resonance Imaging Neural networks Optimization Probabilistic models Retrospective Studies segmentation Semantic segmentation Semantics Spatial data Xenon 129 Xenon Isotopes deep learning Advanced Normalization Tools functional lung imaging segmentation convolutional neural network
ISSN:	0740-3194, 1522-2594, 1522-2594
Online-Zugang:	Volltext
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