126 citations · 219 across the 5 of their papers we have counts for
3 papers · 1 filter
Future-State Predicting LSTM for Early Surgery Type Recognition
Siddharth Kannan, Gaurav Yengera, Didier Mutter +2
This work presents a novel approach for the early recognition of the type of a laparoscopic surgery from its video. Early recognition algorithms can be beneficial to the developmen…
Less is More: Surgical Phase Recognition with Less Annotations through Self-Supervised Pre-training of CNN-LSTM Networks
Gaurav Yengera, Didier Mutter, Jacques Marescaux +1
Real-time algorithms for automatically recognizing surgical phases are needed to develop systems that can provide assistance to surgeons, enable better management of operating room…
RSDNet: Learning to Predict Remaining Surgery Duration from Laparoscopic Videos Without Manual Annotations
Andru Putra Twinanda, Gaurav Yengera, Didier Mutter +2
Accurate surgery duration estimation is necessary for optimal OR planning, which plays an important role in patient comfort and safety as well as resource optimization. It is, howe…