76 citations · 117 across the 4 of their papers we have counts for
4 papers
Three dimensional blind image deconvolution for fluorescence microscopy using generative adversarial networks
Soonam Lee, Shuo Han, Paul Salama +2
Due to image blurring image deconvolution is often used for studying biological structures in fluorescence microscopy. Fluorescence microscopy image volumes inherently suffer from…
Tubule segmentation of fluorescence microscopy images based on convolutional neural networks with inhomogeneity correction
Soonam Lee, Chichen Fu, Paul Salama +2
Fluorescence microscopy has become a widely used tool for studying various biological structures of in vivo tissue or cells. However, quantitative analysis of these biological stru…
Background subtraction using the factored 3-way restricted Boltzmann machines
Soonam Lee, Daekeun Kim
In this paper, we proposed a method for reconstructing the 3D model based on continuous sensory input. The robot can draw on extremely large data from the real world using various…
Three Dimensional Fluorescence Microscopy Image Synthesis and Segmentation
Chichen Fu, Soonam Lee, David Joon Ho +4
Advances in fluorescence microscopy enable acquisition of 3D image volumes with better image quality and deeper penetration into tissue. Segmentation is a required step to characte…