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).
no code implementations • 22 Dec 2020 • Xilin Yang, Luzhe Huang, Yilin Luo, Yichen Wu, Hongda Wang, Yair Rivenson, Aydogan Ozcan
We present a virtual image refocusing method over an extended depth of field (DOF) enabled by cascaded neural networks and a double-helix point-spread function (DH-PSF).
no code implementations • 21 Oct 2020 • Luzhe Huang, Yilin Luo, Yair Rivenson, Aydogan Ozcan
Volumetric imaging of samples using fluorescence microscopy plays an important role in various fields including physical, medical and life sciences.
no code implementations • 21 Mar 2020 • Yilin Luo, Luzhe Huang, Yair Rivenson, Aydogan Ozcan
We demonstrate a deep learning-based offline autofocusing method, termed Deep-R, that is trained to rapidly and blindly autofocus a single-shot microscopy image of a specimen that is acquired at an arbitrary out-of-focus plane.
1 code implementation • 31 Jan 2019 • Yichen Wu, Yair Rivenson, Hongda Wang, Yilin Luo, Eyal Ben-David, Laurent A. Bentolila, Christian Pritz, Aydogan Ozcan
Three-dimensional (3D) fluorescence microscopy in general requires axial scanning to capture images of a sample at different planes.
no code implementations • 17 Nov 2018 • Yichen Wu, Yilin Luo, Gunvant Chaudhari, Yair Rivenson, Ayfer Calis, Kevin De Haan, Aydogan Ozcan
Deep learning brings bright-field microscopy contrast to holographic images of a sample volume, bridging the volumetric imaging capability of holography with the speckle- and artifact-free image contrast of bright-field incoherent microscopy.