We propose 4D spatio-temporal deep learning for OCT-based motion estimation. On a tissue dataset, we find that using 4D information for the model input ...
May 22, 2020 · We investigate whether using a temporal stream of OCT image volumes can improve deep learning-based motion estimation performance. For this ...
[PDF] Spatio-temporal deep learning methods for motion estimation ...
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4D spatio-temporal deep learning for OCT-based motion estimation is proposed and it is found that using 4D information for the model input improves ...
Methods We investigate whether using a temporal stream of OCT image volumes can improve deep learning-based motion estimation performance. For this purpose, we ...
Sep 11, 2024 · Methods. We investigate whether using a temporal stream of OCT image volumes can improve deep learning-based motion estimation performance. For ...
In this work, we extend the problem of deep learning-based force estimation to 4D spatio-temporal data with streams of 3D OCT volumes.
Apr 21, 2020 · We propose 4D spatio-temporal deep learning for end-to-end motion forecasting and estimation using a stream of OCT volumes.
Purpose. Localizing structures and estimating the motion of a specific target region are common problems for navigation during surgical interventions.
May 20, 2020 · OCT can provide. 3D volumes with a rich spatial feature space through subsur- face imaging which can be effectively used by deep learning.
In this work, we propose an end-to-end deep learning approach for motion estimation and forecasting using entire sequences of OCT volumes. So far, 4D deep ...