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Quantitative feature analysis of CT images of transbronchial dye markings mimicking true pulmonary ground-glass opacity lesions
- Publication Year :
- 2019
- Publisher :
- AME Publishing Company, 2019.
-
Abstract
- Background: Transbronchial dye marking is a preoperative localization technique aiding pulmonary resection. Post-marking computed tomography (CT) is performed to confirm the locations of the actual markings. This study aimed to evaluate the CT images of dye markings that present as ground-glass opacities (GGO), using quantitative feature analysis. Methods: Thin-slice (1 mm) CT images of the dye markings and true ground glass nodule (GGN) lesions were obtained for quantitative analysis with gray-level co-occurrence matrix (GLCM) features. The quantification features including correlation, auto correlation, contrast, energy, entropy, and homogeneity were evaluated. Statistical analysis with boxplot was performed. Results: GLCM features of multi-detector computed tomography (MDCT) images of the dye markings (n=13) and true GGN lesions (n=13) differed significantly in contrast, energy, entropy, auto correlation, and homogeneity. Cone beam computed tomographic (CBCT) image features of another group of dye markings (n=15) also showed a different distribution of feature values, than those of the MDCT images. Conclusions: Quantitative analysis of the dye marking images revealed a discriminative variance, compared with those of the true GGN lesions. Furthermore, the image textures of dye markings on MDCT and CBCT also presented with obvious discrepancies.
- Subjects :
- Materials science
medicine.diagnostic_test
business.industry
Computed tomography
General Medicine
030204 cardiovascular system & hematology
Ground-glass opacity
Computed tomographic
03 medical and health sciences
0302 clinical medicine
030228 respiratory system
Feature (computer vision)
medicine
Statistical analysis
Original Article
Pulmonary resection
medicine.symptom
Nuclear medicine
business
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....047d3c944e4f7c4ff3a9fdb7885c0719