activity
20172021
most citedComparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery

48 citations · 132 across the 11 of their papers we have counts for

collaborators

11 papers

eess.IV2021★ 6 cited

Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmark

Martin Wagner, Beat-Peter Müller-Stich, Anna Kisilenko +38

PURPOSE: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase the safety of the…

eess.IV2021★ 7 cited

Machine learning-based analysis of hyperspectral images for automated sepsis diagnosis

Maximilian Dietrich, Silvia Seidlitz, Nicholas Schreck +16

Sepsis is a leading cause of mortality and critical illness worldwide. While robust biomarkers for early diagnosis are still missing, recent work indicates that hyperspectral imagi…

physics.med-ph2020

Tattoo tomography: Freehand 3D photoacoustic image reconstruction with an optical pattern

Niklas Holzwarth, Melanie Schellenberg, Janek Gröhl +6

Purpose: Photoacoustic tomography (PAT) is a novel imaging technique that can spatially resolve both morphological and functional tissue properties, such as the vessel topology and…

cs.CV2020

Heidelberg Colorectal Data Set for Surgical Data Science in the Sensor Operating Room

Lena Maier-Hein, Martin Wagner, Tobias Ross +30

Image-based tracking of medical instruments is an integral part of surgical data science applications. Previous research has addressed the tasks of detecting, segmenting and tracki…

eess.IV2019★ 5 cited

Out of distribution detection for intra-operative functional imaging

Tim J. Adler, Leonardo Ayala, Lynton Ardizzone +6

Multispectral optical imaging is becoming a key tool in the operating room. Recent research has shown that machine learning algorithms can be used to convert pixel-wise reflectance…

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…

cs.HC2018★ 43 cited

IMHOTEP - Virtual Reality Framework for Surgical Applications

Micha Pfeiffer, Hannes Kenngott, Anas Preukschas +4

Purpose: The data which is available to surgeons before, during and after surgery is steadily increasing in quantity as well as diversity. When planning a patient's treatment, this…

cs.CV2017

Exploiting the potential of unlabeled endoscopic video data with self-supervised learning

Tobias Ross, David Zimmerer, Anant Vemuri +12

Surgical data science is a new research field that aims to observe all aspects of the patient treatment process in order to provide the right assistance at the right time. Due to t…

cs.CY2017★ 4 cited

What does it all mean? Capturing Semantics of Surgical Data and Algorithms with Ontologies

Darko Katić, Maria Maleshkova, Sandy Engelhardt +9

Every year approximately 234 million major surgeries are performed, leading to plentiful, highly diverse data. This is accompanied by a matching number of novel algorithms for the…