Abstract
Real-time display of processed en-face spectral domain optical coherence tomography (SD-OCT) images is important for diagnosis. However, due to many steps of data processing requirements, such as Fast Fourier transformation (FFT), data re-sampling, spectral shaping, apodization, zero padding, followed by software cut of the 3D volume acquired to produce an en-face slice, conventional high-speed SD-OCT cannot render an en-face OCT image in real time. Recently we demonstrated a Master/Slave (MS)-OCT method that is highly parallelizable, as it provides reflectivity values of points at depth within an A-scan in parallel. This allows direct production of en-face images. In addition, the MS-OCT method does not require data linearization, which further simplifies the processing. The computation in our previous paper was however time consuming. In this paper we present an optimized algorithm that can be used to provide en-face MS-OCT images much quicker. Using such an algorithm we demonstrate around 10 times faster production of sets of en-face OCT images than previously obtained as well as simultaneous real-time display of up to 4 en-face OCT images of 200 × 200 pixels(2) from the fovea and the optic nerve of a volunteer. We also demonstrate 3D and B-scan OCT images obtained from sets of MS-OCT C-scans, i.e. with no FFT and no intermediate step of generation of A-scans.
Highlights
OCT imaging of the eye fundus is dominated by spectral domain (SD)-OCT methods
We will refer in what follows to both Sp based OCT and swept source (SS) based OCT methods as spectral domain methods of practicing OCT, some reports refer to both methods as Fourier domain OCT [2,5]
There, we introduced a new class of spectral domain interferometry set-ups, made from two interferometers, a Master Interferometer (MI) and a Slave Interferometer (SI)
Summary
OCT imaging of the eye fundus is dominated by spectral domain (SD)-OCT methods. The spectrometer (Sp) based OCT method employs a broadband source and a fast linear camera in a spectrometer [1,2]. The time to produce an en-face image is determined by the time required to collect all volume data plus the time needed to postprocess the acquired data [6] This involves several signal processing steps such as zeropadding, fast Fourier transformation (FFT), data re-sampling (not required when clocked swept sources are employed but compulsory in camera based imaging systems), spectral shaping, apodization as well as rendering of the en-face plane from the 3D volume of A-scans, etc. All these steps on a non-specialized computer, take more time than the time needed to execute a full frame of en-face scanning. A whole set of 36 en face images is obtained in 3 s and real-time generation of en-face images of the eye fundus in-vivo becomes possible, being able to deliver up to four such images in real-time at a rate of 0.6 Hz, or one en-face image at 1 Hz
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