MitoEM Dataset: Large-Scale 3D Mitochondria Instance Segmentation from EM Images

@article{Wei2020MitoEMDL,
  title={MitoEM Dataset: Large-Scale 3D Mitochondria Instance Segmentation from EM Images},
  author={D. Wei and Zudi Lin and Daniel Franco-Barranco and N. Wendt and Xingyu and Liu and Wenjie Yin and Xin Huang and Aarush Gupta and Won-Dong Jang and Xueying Wang and I. Arganda-Carreras and J. Lichtman and H. Pfister},
  journal={Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year={2020},
  volume={12265},
  pages={
          66-76
        }
}
  • D. Wei, Zudi Lin, +11 authors H. Pfister
  • Published 2020
  • Medicine, Computer Science
  • Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Electron microscopy (EM) allows the identification of intracellular organelles such as mitochondria, providing insights for clinical and scientific studies. However, public mitochondria segmentation datasets only contain hundreds of instances with simple shapes. It is unclear if existing methods achieving human-level accuracy on these small datasets are robust in practice. To this end, we introduce the MitoEM dataset, a 3D mitochondria instance segmentation dataset with two (30μm)3 volumes from… Expand

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