18 citations · 19 across the 3 of their papers we have counts for
5 papers
RCNN-SliceNet: A Slice and Cluster Approach for Nuclei Centroid Detection in Three-Dimensional Fluorescence Microscopy Images
Liming Wu, Shuo Han, Alain Chen +3
Robust and accurate nuclei centroid detection is important for the understanding of biological structures in fluorescence microscopy images. Existing automated nuclei localization…
Low-Rank Reorganization via Proportional Hazards Non-negative Matrix Factorization Unveils Survival Associated Gene Clusters
Zhi Huang, Paul Salama, Wei Shao +2
One of the central goals in precision health is the understanding and interpretation of high-dimensional biological data to identify genes and markers associated with disease initi…
Center-Extraction-Based Three Dimensional Nuclei Instance Segmentation of Fluorescence Microscopy Images
David Joon Ho, Shuo Han, Chichen Fu +3
Fluorescence microscopy is an essential tool for the analysis of 3D subcellular structures in tissue. An important step in the characterization of tissue involves nuclei segmentati…
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…