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Found 5 papers, 1 papers with code
Deep learning with 4D spatio-temporal data representations for OCT-based force estimation
Moreover, optical coherence tomography (OCT) and deep learning have been used for estimating forces based on deformation observed in volumetric image data.
Spatio-Temporal Deep Learning Methods for Motion Estimation Using 4D OCT Image Data
For this purpose, we design and evaluate several 3D and 4D deep learning methods and we propose a new deep learning approach.
Towards Automatic Lesion Classification in the Upper Aerodigestive Tract Using OCT and Deep Transfer Learning Methods
As the results were promising, automatic classification of lesions might be feasible which could assist experts in their decision making.
Two-path 3D CNNs for calibration of system parameters for OCT-based motion compensation
Optical coherence tomography (OCT) is an imaging modality which is used in interventions due to its high spatial resolution of few micrometers and its temporal resolution of potentially several hundred volumes per second.
A Deep Learning Approach for Pose Estimation from Volumetric OCT Data
We use this setup to provide an in-depth analysis on deep learning-based pose estimation from volumes.
