A three-dimensional virtual mouse generates synthetic training data for behavioral analysis
We developed a three-dimensional (3D) synthetic animated mouse based on computed tomography scans that is actuated using animation and semirandom, joint-constrained movements to generate synthetic behavioral data with ground-truth label locations. Image-domain translation produced realistic syntheti...
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Veröffentlicht in: | Nature methods 2021-04, Vol.18 (4), p.378-381 |
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creator | Bolaños, Luis A. Xiao, Dongsheng Ford, Nancy L. LeDue, Jeff M. Gupta, Pankaj K. Doebeli, Carlos Hu, Hao Rhodin, Helge Murphy, Timothy H. |
description | We developed a three-dimensional (3D) synthetic animated mouse based on computed tomography scans that is actuated using animation and semirandom, joint-constrained movements to generate synthetic behavioral data with ground-truth label locations. Image-domain translation produced realistic synthetic videos used to train two-dimensional (2D) and 3D pose estimation models with accuracy similar to typical manual training datasets. The outputs from the 3D model-based pose estimation yielded better definition of behavioral clusters than 2D videos and may facilitate automated ethological classification.
Bolaños et al. present a realistic three-dimensional virtual mouse model that can be animated and that facilitates the training of pose estimation algorithms. |
doi_str_mv | 10.1038/s41592-021-01103-9 |
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Bolaños et al. present a realistic three-dimensional virtual mouse model that can be animated and that facilitates the training of pose estimation algorithms.</description><subject>631/114/1564</subject><subject>631/1647/2198</subject><subject>631/1647/334/1874/345</subject><subject>631/1647/794</subject><subject>631/378/2632</subject><subject>Algorithms</subject><subject>Animal models</subject><subject>Animal models in research</subject><subject>Animals</subject><subject>Animation</subject><subject>Behavior</subject><subject>Behavior, Animal</subject><subject>Behavioral assessment</subject><subject>Bioinformatics</subject><subject>Biological Microscopy</subject><subject>Biological Techniques</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedical Engineering/Biotechnology</subject><subject>Brief Communication</subject><subject>Cameras</subject><subject>Computed tomography</subject><subject>Computer simulation</subject><subject>CT 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Image-domain translation produced realistic synthetic videos used to train two-dimensional (2D) and 3D pose estimation models with accuracy similar to typical manual training datasets. The outputs from the 3D model-based pose estimation yielded better definition of behavioral clusters than 2D videos and may facilitate automated ethological classification.
Bolaños et al. present a realistic three-dimensional virtual mouse model that can be animated and that facilitates the training of pose estimation algorithms.</abstract><cop>New York</cop><pub>Nature Publishing Group US</pub><pmid>33820989</pmid><doi>10.1038/s41592-021-01103-9</doi><tpages>4</tpages><orcidid>https://orcid.org/0000-0001-6814-2812</orcidid><orcidid>https://orcid.org/0000-0002-0093-4490</orcidid><orcidid>https://orcid.org/0000-0002-1669-0021</orcidid><orcidid>https://orcid.org/0000-0003-2692-0801</orcidid><oa>free_for_read</oa></addata></record> |
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title | A three-dimensional virtual mouse generates synthetic training data for behavioral analysis |
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