Research

1

  • Removing Imaging Artifacts in Electron Microscopy using an Asymmetrically Cyclic Adversarial Network without Paired Training Data. [Read more.]
  • Accurate cancer type classification based on somatic alterations using an ensemble of a random forest and a deep neural network. [Read more.]
  • Gene Mutation Detection in Biliary Tract Cancer. [Read more.]
  • Weakly Supervised Learning in Deformable EM Image Registration using Slice Interpolation. [Read more.]
  • Bright-Field to Fluorescence Microscopy Image Conversion Using Deep Learning for Label-Free High-Content Screening. [Read more.]
  • Convolutional Sparse Coding for Cell Segmentation in Microscopy Images. [Read more.]
  • GPU Computing for Medical Image Analysis. [Read more.]

2

3

  • High-performance computing for viscosity solution. [Read more.]
  • Visual and Scientific computing in MapReduce framework. [Read more.]