Neural network-based image reconstruction in swept-source optical coherence tomography using undersampled spectral data

no code implementations • 4 Mar 2021 • Yijie Zhang, Tairan Liu, Manmohan Singh, Yilin Luo, Yair Rivenson, Kirill V. Larin, Aydogan Ozcan

Using 2-fold undersampled spectral data (i. e., 640 spectral points per A-line), the trained neural network can blindly reconstruct 512 A-lines in ~6. 73 ms using a desktop computer, removing spatial aliasing artifacts due to spectral undersampling, also presenting a very good match to the images of the same samples, reconstructed using the full spectral OCT data (i. e., 1280 spectral points per A-line).

Image Reconstruction