scholarly journals Uncertainty-Aware Organ Classification for Surgical Data Science Applications in Laparoscopy

2018 ◽  
Vol 65 (11) ◽  
pp. 2649-2659 ◽  
Author(s):  
Sara Moccia ◽  
Sebastian J. Wirkert ◽  
Hannes Kenngott ◽  
Anant S. Vemuri ◽  
Martin Apitz ◽  
...  
2021 ◽  
pp. 102306
Author(s):  
Lena Maier-Hein ◽  
Matthias Eisenmann ◽  
Duygu Sarikaya ◽  
Keno März ◽  
Toby Collins ◽  
...  

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Lena Maier-Hein ◽  
Martin Wagner ◽  
Tobias Ross ◽  
Annika Reinke ◽  
Sebastian Bodenstedt ◽  
...  

AbstractImage-based tracking of medical instruments is an integral part of surgical data science applications. Previous research has addressed the tasks of detecting, segmenting and tracking medical instruments based on laparoscopic video data. However, the proposed methods still tend to fail when applied to challenging images and do not generalize well to data they have not been trained on. This paper introduces the Heidelberg Colorectal (HeiCo) data set - the first publicly available data set enabling comprehensive benchmarking of medical instrument detection and segmentation algorithms with a specific emphasis on method robustness and generalization capabilities. Our data set comprises 30 laparoscopic videos and corresponding sensor data from medical devices in the operating room for three different types of laparoscopic surgery. Annotations include surgical phase labels for all video frames as well as information on instrument presence and corresponding instance-wise segmentation masks for surgical instruments (if any) in more than 10,000 individual frames. The data has successfully been used to organize international competitions within the Endoscopic Vision Challenges 2017 and 2019.


Author(s):  
Gregory D. Hager ◽  
Lena Maier-Hein ◽  
S. Swaroop Vedula

2021 ◽  
Vol 124 (2) ◽  
pp. 221-230
Author(s):  
Thomas M. Ward ◽  
Pietro Mascagni ◽  
Amin Madani ◽  
Nicolas Padoy ◽  
Silvana Perretta ◽  
...  

2017 ◽  
Vol 1 (9) ◽  
pp. 691-696 ◽  
Author(s):  
Lena Maier-Hein ◽  
Swaroop S. Vedula ◽  
Stefanie Speidel ◽  
Nassir Navab ◽  
Ron Kikinis ◽  
...  

2021 ◽  
Vol 2 (3) ◽  
pp. 321-332
Author(s):  
Julian Klodmann ◽  
Christopher Schlenk ◽  
Anja Hellings-Kuß ◽  
Thomas Bahls ◽  
Roland Unterhinninghofen ◽  
...  

Abstract Purpose of Review Robotic assistance systems for diagnosis and therapy have become technically mature and widely available. Thus, they play an increasingly important role in patient care. This paper provides an overview of the general concepts of robotically assisted surgical systems, briefly revisiting historical and current developments in the surgical robotics market and discussing current focus areas of research. Comprehensiveness cannot be achieved in this format, but besides the general overview, references to further readings and more comprehensive reviews with regard to particular aspects are given. Therefore, the work at hand is considered as an introductory paper into the topic and especially addresses investigators, researchers, medical device manufacturers, and clinicians, who are new to this field. Recent Findings The current research in Robotically Assisted Surgical Systems (RASS) increasingly uses established robotic platforms. To minimize the patient trauma while optimizing the dexterity of the surgeon, miniaturized instruments and semi-autonomous assistance functions are developed. To provide the surgeon with all necessary information in an adequate manner, novel imaging sensors as well as techniques for multimodal sensory feedback and augmented reality are investigated. The Surgical Data Science applies data management and processing approaches including machine learning on medical data to provide optimal, individualized and contextual support to the surgeon. Summary Robotic systems will significantly influence future patient care. Since they must fulfill manifold medical, technical, regulatory and economic requirements, their development calls for a close, active and interdisciplinary cooperation between stakeholders from hospitals, industry and science.


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