Three Dimensional Fluorescence Microscopy Image Synthesis and Segmentation

@article{Fu2018ThreeDF,
  title={Three Dimensional Fluorescence Microscopy Image Synthesis and Segmentation},
  author={Chichen Fu and Soonam Lee and David Joon Ho and Shuo Han and Paul Salama and Kenneth W. Dunn and Edward J. Delp},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  year={2018},
  pages={2302-23028}
}
  • Chichen FuSoonam Lee E. Delp
  • Published 22 January 2018
  • Computer Science
  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Advances in fluorescence microscopy enable acquisition of 3D image volumes with better image quality and deeper penetration into tissue. [] Key Method A set of synthetic volumes and the corresponding groundtruth are generated using spatially constrained cycle-consistent adversarial networks. Segmentation results demonstrate that our proposed method is capable of segmenting nuclei successfully for various data sets.

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