Classification of computed tomography scanner manufacturer using support vector machine: Investigation of manufacturer-related differences in density distribution

Seung Bo Lee, Eun Jin Jeong, Yunsik Son, Dong Ju Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Computed tomography (CT) is useful to investigate the presence and severity of injury during acute stage of traumatic brain injury (TBI) due to its availability and short image acquisition time. Recently, quantitative CT analysis have shown promising results in objective and accurate assessment of lesion and the prediction of outcome. To conduct further multicenter, longitudinal follow-up studies using quantitative analysis, the effect of CT scanner manufacturer should be investigated. In this study, CT images were acquired from 326 subjects without any apparent intracranial abnormalities. The images were scanned by three different scanner manufacturers. The quantitative analysis was performed and plotted as density distribution. The acquired density distributions were served as input features of support vector machine (SVM) using Gaussian kernet function, which is designed for c1assifying the CT images based on the scanner manufacturers. The optimal hyperparameters were explored via grid search test and the model increased the robustness by 5-fold cross validation. The best predictive performance was obtained when C = 100 and "I = 0.1 (accuracy = 91.1 %). The resuIts showed significant difference in density distribution according to the scanner manufacturers, and thus suggest that the manufacturer should be standardized to conduct the quantitative analysis on the brain CT images.

Original languageEnglish
Title of host publication5th International Winter Conference on Brain-Computer Interface, BCI 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages85-87
Number of pages3
ISBN (Electronic)9781509050963
DOIs
Publication statusPublished - 2017 Feb 16
Event5th International Winter Conference on Brain-Computer Interface, BCI 2017 - Gangwon Province, Korea, Republic of
Duration: 2017 Jan 92017 Jan 11

Other

Other5th International Winter Conference on Brain-Computer Interface, BCI 2017
CountryKorea, Republic of
CityGangwon Province
Period17/1/917/1/11

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Keywords

  • Computed tomography
  • Quantitative analysis
  • Support vector mahcine
  • Traumatic brain injury

ASJC Scopus subject areas

  • Signal Processing
  • Human-Computer Interaction

Cite this

Lee, S. B., Jeong, E. J., Son, Y., & Kim, D. J. (2017). Classification of computed tomography scanner manufacturer using support vector machine: Investigation of manufacturer-related differences in density distribution. In 5th International Winter Conference on Brain-Computer Interface, BCI 2017 (pp. 85-87). [7858167] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWW-BCI.2017.7858167