4 citations · 12 across the 5 of their papers we have counts for
5 papers
De-Noising of Photoacoustic Microscopy Images by Deep Learning
Da He, Jiasheng Zhou, Xiaoyu Shang +2
As a hybrid imaging technology, photoacoustic microscopy (PAM) imaging suffers from noise due to the maximum permissible exposure of laser intensity, attenuation of ultrasound in t…
Adherent Mist and Raindrop Removal from a Single Image Using Attentive Convolutional Network
Da He, Xiaoyu Shang, Jiajia Luo
Temperature difference-induced mist adhered to the glass, such as windshield, camera lens, is often inhomogeneous and obscure, easily obstructing the vision and severely degrading…
Photoacoustic Microscopy with Sparse Data Enabled by Convolutional Neural Networks for Fast Imaging
Jiasheng Zhou, Da He, Xiaoyu Shang +3
Photoacoustic microscopy (PAM) has been a promising biomedical imaging technology in recent years. However, the point-by-point scanning mechanism results in low-speed imaging, whic…
Miniature Probe for Optomechanical Focus-adjustable Optical-resolution Photoacoustic Endoscopy
Zhendong Guo, Zhanhong Ye, Weihao Shao +2
Photoacoustic microscopy (PAM) is a promising imaging modality because it is able to reveal optical absorption contrast in high resolution on the order of a micrometer. It can be a…
Adaptive Weighting Depth-variant Deconvolution of Fluorescence Microscopy Images with Convolutional Neural Network
Da He, De Cai, Jiasheng Zhou +2
Fluorescence microscopy plays an important role in biomedical research. The depth-variant point spread function (PSF) of a fluorescence microscope produces low-quality images espec…