GPU-accelerated non-uniform fast Fourier transform-based compressive sensing spectral domain optical coherence tomography

Abstract

We implemented the graphics processing unit (GPU) accelerated compressive sensing (CS) non-uniform in k-space spectral domain optical coherence tomography (SD OCT). Kaiser-Bessel (KB) function and Gaussian function are used independently as the convolution kernel in the gridding-based non-uniform fast Fourier transform (NUFFT) algorithm with different oversampling ratios and kernel widths. Our implementation is compared with the GPU-accelerated modified non-uniform discrete Fourier transform (MNUDFT) matrix-based CS SD OCT and the GPU-accelerated fast Fourier transform (FFT)-based CS SD OCT. It was found that our implementation has comparable performance to the GPU-accelerated MNUDFT-based CS SD OCT in terms of image quality while providing more than 5 times speed enhancement. When compared to the GPU-accelerated FFT based-CS SD OCT, it shows smaller background noise and less side lobes while eliminating the need for the cumbersome k-space grid filling and the k-linear calibration procedure. Finally, we demonstrated that by using a conventional desktop computer architecture having three GPUs, real-time B-mode imaging can be obtained in excess of 30 fps for the GPU-accelerated NUFFT based CS SD OCT with frame size 2048(axial) × 1,000(lateral).

Fig. 1

Sparsity comparison of A-scans by applying (a) NUDFT, (b) MNUDFT, (c) type-1 NUFFT to the full-length nonlinear wavenumber spectral data, and (d) FFT to the full-length linear wavenumber spectral data.

Fig. 2

Sensitivity roll-off of different processing methods: (a) NUDFT on 100% data; (b) FFT-CS; (c) MNUDFT-CS; (d) NUFFT-CS with Gaussian kernel (R=2, W=5); (e) NUFFT-CS with KB kernel (R=2, W=5); (f) NUFFT-CS with KB kernel (R=1.5, W=3). (g) comparison of PSFs at a certain image depth using different processing methods; (h) maximum amplitude of PSFs using different processing methods; (i) SNR versus image depth for different processing methods.

Fig. 3

B-scans of an orange: (a) original image; (b) NUFFT-CS reconstruction result (see Media 1 for real-time imaging display), and human skin: (c) original image; (d) NUFFT-CS reconstruction result (see Media 2 for real-time imaging display). The scale bars represent 100 μm. The image size is 900(axial)×950(lateral).