Deep-learning-based motion-correction algorithm in optical resolution photoacoustic microscopy
Abstract In this study, we propose a deep-learning-based method to correct motion artifacts in optical resolution photoacoustic microscopy (OR-PAM). The method is a convolutional neural network that establishes an end-to-end map from input raw data with motion artifacts to output corrected images. F...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2019-10-01
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| Series: | Visual Computing for Industry, Biomedicine, and Art |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s42492-019-0022-9 |