SIFT-GVF-based lung edge correction method for correcting the lung region in CT images

Juxtapleural nodules were excluded from the segmented lung region in the Hounsfield unit threshold-based segmentation method. To re-include those regions in the lung region, a new approach was presented using scale-invariant feature transform and gradient vector flow models in this study. First, the...

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Bibliographic Details
Published in:PloS one 2023-02, Vol.18 (2), p.e0282107-e0282107
Main Authors: Li, Xin, Feng, Bin, Qiao, Sai, Wei, Haiyan, Feng, Changli
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Automation
Biology and Life Sciences
Cerebellar Vermis
Computed tomography
Computer and Information Sciences
CT imaging
Image segmentation
Invariants
Lung - diagnostic imaging
Lung cancer
Lung diseases
Lungs
Medical imaging
Medical screening
Medicine and Health Sciences
Methods
Neural networks
Nodules
Physical Sciences
Prevention
Pulmonary function tests
Research and Analysis Methods
Risk factors
Thorax
Tomography, X-Ray Computed
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Summary:Juxtapleural nodules were excluded from the segmented lung region in the Hounsfield unit threshold-based segmentation method. To re-include those regions in the lung region, a new approach was presented using scale-invariant feature transform and gradient vector flow models in this study. First, the scale-invariant feature transform method was utilized to detect all scale-invariant points in the binary lung region. The boundary points in the neighborhood of a scale-invariant point were collected to form the supportive boundary lines. Then, we utilized a Fourier descriptor to obtain a character representation of each supportive boundary line. Spectrum energy recognizes supportive boundaries that must be corrected. Third, the gradient vector flow-snake method was presented to correct the recognized supportive borders with a smooth profile curve, giving an ideal correction edge in those regions. Finally, the performance of the proposed method was evaluated through experiments on multiple authentic computed tomography images. The perfect results and robustness proved that the proposed method could correct the juxtapleural region precisely.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0282107