• Corpus ID: 3854002

Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation

@article{Stollenga2015ParallelML,
  title={Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation},
  author={Marijn F. Stollenga and Wonmin Byeon and Marcus Liwicki and J{\"u}rgen Schmidhuber},
  journal={ArXiv},
  year={2015},
  volume={abs/1506.07452}
}
Convolutional Neural Networks (CNNs) can be shifted across 2D images or 3D videos to segment them. [] Key Method Here we re-arrange the traditional cuboid order of computations in MD-LSTM in pyramidal fashion. The resulting PyraMiD-LSTM is easy to parallelise, especially for 3D data such as stacks of brain slice images. PyraMiD-LSTM achieved best known pixel-wise brain image segmentation results on MRBrainS13 (and competitive results on EM-ISBI12).

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