Quality assessment for spectral domain optical coherence tomography (OCT) images

Abstract

Retinal nerve fiber layer (RNFL) thickness, a measure of glaucoma progression, can be measured in images acquired by spectral domain optical coherence tomography (OCT). The accuracy of RNFL thickness estimation, however, is affected by the quality of the OCT images. In this paper, a new parameter, signal deviation (SD), which is based on the standard deviation of the intensities in OCT images, is introduced for objective assessment of OCT image quality. Two other objective assessment parameters, signal to noise ratio (SNR) and signal strength (SS), are also calculated for each OCT image. The results of the objective assessment are compared with subjective assessment. In the subjective assessment, one OCT expert graded the image quality according to a three-level scale (good, fair, and poor). The OCT B-scan images of the retina from six subjects are evaluated by both objective and subjective assessment. From the comparison, we demonstrate that the objective assessment successfully differentiates between the acceptable quality images (good and fair images) and poor quality OCT images as graded by OCT experts. We evaluate the performance of the objective assessment under different quality assessment parameters and demonstrate that SD is the best at distinguishing between fair and good quality images. The accuracy of RNFL thickness estimation is improved significantly after poor quality OCT images are rejected by automated objective assessment using the SD, SNR, and SS.

Figures

Figure 1

High resolution OCT image of in vivo primate retina demonstrating morphological features. Retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer (INL), outer plexiform layer (OPL), outer nuclear layer (onl/pr), pigment epithelium (PE), choroid (CH) and optic nerve head (ONH) are shown in this image. The system probes the eye to a depth of 1mm over a field 4mm wide.

Figure 2

Edge detection results of a poor quality image. The top image is the original OCT intensity image. The bottom image is the result of the edge detection of the top image.

Figure 3

Line-scanning laser ophthalmoscope (LSLO) image of an eye. Spectral domain OCT system is used to take ring scans within the ring region between two red circles.

Figure 4

The top panel is the original OCT image. The bottom panel is the binary mask from adaptive thresholding.

Figure 5

Example of good, fair, and poor quality OCT images. The top one is good quality image: SNR=6.61, SS=104.85, and SD=7.50. The middle one is fair quality image: SNR=5.69, SS=97.49, and SD=10.70. The bottom one is poor quality image SNR=4.01, SS=75.66, and SD=15.70.