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Found 5 papers, 0 papers with code
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.
Real-time image-based instrument classification for laparoscopic surgery
On manually provided bounding boxes, we achieve a instrument type recognition rate of up to 58% and on automatically detected bounding boxes up to 49%.
Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery
The paper presents a comparative validation study of different vision-based methods for instrument segmentation and tracking in the context of robotic as well as conventional laparoscopic surgery.
Unsupervised temporal context learning using convolutional neural networks for laparoscopic workflow analysis
In this paper, we address this problem by presenting an unsupervised method for training a convolutional neural network (CNN) to differentiate between laparoscopic video frames on a temporal basis.
