54 citations · 54 across the 1 of their papers we have counts for
7 papers
Neural network-based image reconstruction in swept-source optical coherence tomography using undersampled spectral data
Yijie Zhang, Tairan Liu, Manmohan Singh +4
Optical Coherence Tomography (OCT) is a widely used non-invasive biomedical imaging modality that can rapidly provide volumetric images of samples. Here, we present a deep learning…
Holographic image reconstruction with phase recovery and autofocusing using recurrent neural networks
Luzhe Huang, Tairan Liu, Xilin Yang +3
Digital holography is one of the most widely used label-free microscopy techniques in biomedical imaging. Recovery of the missing phase information of a hologram is an important st…
Deep learning-based holographic polarization microscopy
Tairan Liu, Kevin de Haan, Bijie Bai +8
Polarized light microscopy provides high contrast to birefringent specimen and is widely used as a diagnostic tool in pathology. However, polarization microscopy systems typically…
Deep learning-based color holographic microscopy
Tairan Liu, Zhensong Wei, Yair Rivenson +4
We report a framework based on a generative adversarial network (GAN) that performs high-fidelity color image reconstruction using a single hologram of a sample that is illuminated…
Deep learning-based super-resolution in coherent imaging systems
Tairan Liu, Kevin de Haan, Yair Rivenson +4
We present a deep learning framework based on a generative adversarial network (GAN) to perform super-resolution in coherent imaging systems. We demonstrate that this framework can…
Accurate color imaging of pathology slides using holography and absorbance spectrum estimation of histochemical stains
Yibo Zhang, Tairan Liu, Yujia Huang +6
Holographic microscopy presents challenges for color reproduction due to the usage of narrow-band illumination sources, which especially impacts the imaging of stained pathology sl…