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Found 10 papers, 6 papers with code
Long-Term Temporally Consistent Unpaired Video Translation from Simulated Surgical 3D Data
However for transfer from simulated to photorealistic sequences, available information on the underlying geometry offers potential for achieving global consistency across views.
Rethinking Anticipation Tasks: Uncertainty-aware Anticipation of Sparse Surgical Instrument Usage for Context-aware Assistance
We propose a novel learning task for anticipation of instrument usage in laparoscopic videos that overcomes these limitations.
Non-Rigid Volume to Surface Registration using a Data-Driven Biomechanical Model
In this work, we train a convolutional neural network to perform both the search for surface correspondences as well as the non-rigid registration in one step.
Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration
Using our unsupervised method as an auxiliary task for RSD training, we outperform other self-supervised methods and are comparable to the supervised state-of-the-art.
Using 3D Convolutional Neural Networks to Learn Spatiotemporal Features for Automatic Surgical Gesture Recognition in Video
However, surgical gesture recognition based only on video is a challenging problem that requires effective means to extract both visual and temporal information from the video.
Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation
We show that this data set can be used to train models for the task of liver segmentation of laparoscopic images.
Video-based surgical skill assessment using 3D convolutional neural networks
In contrast, we investigate a method for automatic, objective skill assessment that requires video data only.
Prediction of laparoscopic procedure duration using unlabeled, multimodal sensor data
During laparoscopic interventions, the endoscopic video stream is an ideal source of such information.
Active Learning using Deep Bayesian Networks for Surgical Workflow Analysis
For many applications in the field of computer assisted surgery, such as providing the position of a tumor, specifying the most probable tool required next by the surgeon or determining the remaining duration of surgery, methods for surgical workflow analysis are a prerequisite.
Temporal coherence-based self-supervised learning for laparoscopic workflow analysis
To achieve this, methods for surgical workflow analysis are crucial.
