Synthetic Images for the Semantic Segmentation of Robotic Instruments in a Head Phantom

Citation Author(s):
Saul Alexis
Heredia Perez
The University of Tokyo
Murilo
Marques Marinho
The University of Tokyo
Kanako
Harada
The University of Tokyo
Mamoru
Mitsuishi
The University of Tokyo
Submitted by:
Murilo Marinho
Last updated:
Mon, 05/18/2020 - 23:36
DOI:
10.21227/xmc2-1v59
Links:
Compatible code at Github
License:
Creative Commons Attribution
312 Views
Categories:
Artificial Intelligence
Machine Learning
Keywords:
Medical Robotics
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Abstract 

This dataset was used and described in detail in the following publication. The Effects of Different Levels of Realism on the Training of CNNs with only Synthetic Images for the Semantic Segmentation of Robotic Instruments in a Head Phantom. Heredia-Perez, S. A.; Marinho, M. M.; Harada, K.; and Mitsuishi, M. International Journal of Computer Assisted Radiology and Surgery (IJCARS). 2020. https://doi.org/10.1007/s11548-020-02185-0

Instructions: 

Refer to https://github.com/mmmarinho/levels-of-realism-ijcars2020 for detailed instructions.

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