3D Semantic Mapping from Arthroscopy Using Out-of-Distribution Pose and Depth and In-Distribution Segmentation Training-Reference-Cited by-同舟云学术

3D Semantic Mapping from Arthroscopy Using Out-of-Distribution Pose and Depth and In-Distribution Segmentation Training

Published:2021 Issue: Volume: Page:383-393
ISSN:0302-9743
Container-title:Medical Image Computing and Computer Assisted Intervention – MICCAI 2021
language:
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Author:

Jonmohamadi Yaqub,Ali Shahnewaz,Liu Fengbei,Roberts Jonathan,Crawford Ross,Carneiro Gustavo,Pandey Ajay K.

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-87196-3_36

Reference31 articles.

1. Ali, S., Jonmohamadi, Y., Roberts, J., Crawford, R., Carneiro, G., Pandey, A.K.: Arthroscopic multi-spectral scene segmentation using deep learning. arXiv preprint arXiv:2001.05566 (2021)

2. Ali, S., Jonmohamadi, Y., Takeda, Y., Roberts, J., Crawford, R., Pandey, A.K.: Supervised scene illumination control in stereo arthroscopes for robot assisted minimally invasive surgery. IEEE Sens. J. 4(10), 11577–11587 (2020)

3. Lecture Notes in Computer Science;G Bae,2020

4. Chen, R.J., Bobrow, T.L., Athey, T., Mahmood, F., Durr, N.J.: Slam endoscopy enhanced by adversarial depth prediction. arXiv preprint arXiv:1907.00283 (2019)

5. Da, K.: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)

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