activity
20172024
most citedSurgical Data Science: Enabling Next-Generation Surgery

578 citations · 851 across the 18 of their papers we have counts for

collaborators
Showing 2018Show all

5 papers · 1 filter

cs.CV2018

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…

cs.CV2018★ 1 cited

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…

cs.CV2018★ 9 cited

Real-time image-based instrument classification for laparoscopic surgery

Sebastian Bodenstedt, Antonia Ohnemus, Darko Katic +6

During laparoscopic surgery, context-aware assistance systems aim to alleviate some of the difficulties the surgeon faces. To ensure that the right information is provided at the r…

cs.CY2018★ 10 cited

Surgical Data Science: A Consensus Perspective

Lena Maier-Hein, Matthias Eisenmann, Carolin Feldmann +25

Surgical data science is a scientific discipline with the objective of improving the quality of interventional healthcare and its value through capturing, organization, analysis, a…

cs.CV2018★ 48 cited

Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery

Sebastian Bodenstedt, Max Allan, Anthony Agustinos +17

Intraoperative segmentation and tracking of minimally invasive instruments is a prerequisite for computer- and robotic-assisted surgery. Since additional hardware like tracking sys…