6 papers · 1 filter
Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration
Dominik Rivoir, Sebastian Bodenstedt, Felix von Bechtolsheim +3
Estimating the remaining surgery duration (RSD) during surgical procedures can be useful for OR planning and anesthesia dose estimation. With the recent success of deep learning-ba…
Using 3D Convolutional Neural Networks to Learn Spatiotemporal Features for Automatic Surgical Gesture Recognition in Video
Isabel Funke, Sebastian Bodenstedt, Florian Oehme +3
Automatically recognizing surgical gestures is a crucial step towards a thorough understanding of surgical skill. Possible areas of application include automatic skill assessment,…
Video-based surgical skill assessment using 3D convolutional neural networks
Isabel Funke, Sören Torge Mees, Jürgen Weitz +1
Purpose: A profound education of novice surgeons is crucial to ensure that surgical interventions are effective and safe. One important aspect is the teaching of technical skills f…
Prediction of laparoscopic procedure duration using unlabeled, multimodal sensor data
Sebastian Bodenstedt, Martin Wagner, Lars Mündermann +6
Purpose The course of surgical procedures is often unpredictable, making it difficult to estimate the duration of procedures beforehand. A context-aware method that analyses the wo…
Active Learning using Deep Bayesian Networks for Surgical Workflow Analysis
Sebastian Bodenstedt, Dominik Rivoir, Alexander Jenke +6
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 determ…
Temporal coherence-based self-supervised learning for laparoscopic workflow analysis
Isabel Funke, Alexander Jenke, Sören Torge Mees +3
In order to provide the right type of assistance at the right time, computer-assisted surgery systems need context awareness. To achieve this, methods for surgical workflow analysi…