Abstract
The automatic reconstruction of single neuron cells from microscopic images is essential to establishing the research on neuron morphology. However, the performance of single neuron reconstruction algorithms is constrained by both the quantity and the quality of the annotated 3D microscopic images since annotating large-scale single neuron models is highly labour intensive. We propose a framework for synthesizing microscopy-realistic 3D neuron images from simulated single neuron skeletons using conditional Generative Adversarial Networks (cGAN). We build the generator network with multi-resolution sub-modules to improve the output fidelity. We evaluate our framework on Janelia-Fly dataset from the BigNeuron project. With both qualitative and quantitative analysis, we show that the proposed framework outperforms the other state-of-the-art methods regarding the quality of the synthetic neuron images. We also show that combining the real neuron images and the synthetic images generated from our framework can improve the performance of neuron segmentation.
Original language | English |
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Title of host publication | Proceedings of 2020 IEEE International Symposium on Biomedical Imaging, ISBI 2020 |
Editors | Michael Liebling, Hayit Greenspan |
Place of Publication | USA |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 1775-1779 |
Number of pages | 5 |
Edition | 1st |
ISBN (Electronic) | 9781538693308 |
DOIs | |
Publication status | Published - Apr 2020 |
Externally published | Yes |
Event | IEEE International Symposium on Biomedical Imaging (ISBI) 2020 - Iowa City, United States of America Duration: 3 Apr 2020 → 7 Apr 2020 Conference number: 17th https://ieeexplore.ieee.org/xpl/conhome/9091448/proceeding (Proceedings) |
Publication series
Name | Proceedings - International Symposium on Biomedical Imaging |
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Volume | 2020-April |
ISSN (Print) | 1945-7928 |
ISSN (Electronic) | 1945-8452 |
Conference
Conference | IEEE International Symposium on Biomedical Imaging (ISBI) 2020 |
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Abbreviated title | ISBI 2020 |
Country/Territory | United States of America |
City | Iowa City |
Period | 3/04/20 → 7/04/20 |
Internet address |
Keywords
- Data Augmentation
- Image Synthesis
- Neuron Image