PURPOSE: The purpose of this article was to assess signal quality of retinal optical coherence tomography (OCT) images from multiple devices using subjective and quantitative measurements. METHODS: A total of 120 multiframe OCT images from 4 spectral domain OCT devices (Cirrus, RTVue, Spectralis, and 3D OCT-1000) were evaluated subjectively by trained graders, and measured quantitatively using a derived parameter, maximum tissue contrast index (mTCI). An intensity histogram decomposition model was proposed to separate the foreground and background information of OCT images and to calculate the mTCI. The mTCI results were compared with the manufacturer signal index (MSI) provided by the respective devices, and to the subjective grading scores (SGS). RESULTS: Statistically significant correlations were observed between the paired methods (i.e., SGS and MSI, SGS and mTCI, and mTCI and MSI). Fisher's Z transformation indicated the Pearson correlation coefficient ρ ≥ 0.8 for all devices. Using the Deming regression, correlation parameters between the paired methods were established. This allowed conversion from the proprietary MSI values to SGS and mTCI that are universally applied to each device. CONCLUSIONS: The study suggests signal quality of retinal OCT images can be evaluated subjectively and objectively, independent of the devices. Together with the proposed histogram decomposition model, mTCI may be used as a standardization metric for OCT signal quality that would affect measurements.
PURPOSE: The purpose of this article was to assess signal quality of retinal optical coherence tomography (OCT) images from multiple devices using subjective and quantitative measurements. METHODS: A total of 120 multiframe OCT images from 4 spectral domain OCT devices (Cirrus, RTVue, Spectralis, and 3D OCT-1000) were evaluated subjectively by trained graders, and measured quantitatively using a derived parameter, maximum tissue contrast index (mTCI). An intensity histogram decomposition model was proposed to separate the foreground and background information of OCT images and to calculate the mTCI. The mTCI results were compared with the manufacturer signal index (MSI) provided by the respective devices, and to the subjective grading scores (SGS). RESULTS: Statistically significant correlations were observed between the paired methods (i.e., SGS and MSI, SGS and mTCI, and mTCI and MSI). Fisher's Z transformation indicated the Pearson correlation coefficient ρ ≥ 0.8 for all devices. Using the Deming regression, correlation parameters between the paired methods were established. This allowed conversion from the proprietary MSI values to SGS and mTCI that are universally applied to each device. CONCLUSIONS: The study suggests signal quality of retinal OCT images can be evaluated subjectively and objectively, independent of the devices. Together with the proposed histogram decomposition model, mTCI may be used as a standardization metric for OCT signal quality that would affect measurements.
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