Surgical data science for next-generation interventions.
Lena Maier-Hein,Swaroop Vedula,Stefanie Speidel,Nassir Navab,Nassir Navab,Ron Kikinis,Ron Kikinis,Adrian Park,Matthias Eisenmann,Hubertus Feussner,Germain Forestier,Stamatia Giannarou,Makoto Hashizume,Darko Katic,Hannes Kenngott,Michael Kranzfelder,Anand Malpani,Keno März,Thomas Neumuth,Nicolas Padoy,Carla M. Pugh,Nicolai Schoch,Danail Stoyanov,Russell H. Taylor,Martin Wagner,Gregory D. Hager,Pierre Jannin,Pierre Jannin +27 more
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TLDR
Interventional healthcare will evolve from an artisanal craft based on the individual experiences, preferences and traditions of physicians into a discipline that relies on objective decision-making on the basis of large-scale data from heterogeneous sources.Abstract:
Interventional healthcare will evolve from an artisanal craft based on the individual experiences, preferences and traditions of physicians into a discipline that relies on objective decision-making on the basis of large-scale data from heterogeneous sources.read more
Citations
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Proceedings Article
A Multi Instance Learning Approach for Critical View of Safety Detection in Laparoscopic Cholecystectomy
TL;DR: In this article , an attention-based multi-instance learning (MIL) model was proposed to detect critical view of safety (CVS) in Laparoscopic Cholecystectomy (LC) videos.
Journal ArticleDOI
LABRAD-OR: Lightweight Memory Scene Graphs for Accurate Bimodal Reasoning in Dynamic Operating Rooms
TL;DR: In this paper , the authors propose to use temporal information for more accurate and consistent holistic OR modeling, where the scene graphs of previous time steps act as the temporal representation guiding the current prediction.
Journal ArticleDOI
Analysing multi-perspective patient-related data during laparoscopic gynaecology procedures
Nour Aldeen Jalal,Tamer Abdulbaki Alshirbaji,Bernhard Laufer,Paul D. Docherty,Thomas Neumuth,Knut Moeller +5 more
TL;DR: In this paper , a descriptive analysis of data collected from anaesthesiology and surgery was performed to investigate the relationships between the intra-abdominal pressure (IAP) and lung mechanics for patients during laparoscopic procedures.
Journal ArticleDOI
TEsoNet: knowledge transfer in surgical phase recognition from laparoscopic sleeve gastrectomy to the laparoscopic part of Ivor–Lewis esophagectomy
J. A. Eckhoff,Y. Ban,G. Rosman,Dolores T Müller,D. A. Hashimoto,E. Witkowski,Benjamin Babic,Christiane J. Bruns,Hans F. Fuchs,Ozanan R. Meireles +9 more
TL;DR: In this paper , the knowledge transfer capability of an established model architecture for phase recognition (CNN + LSTM) was adapted to generate a "Transferal Esophagectomy Network" (TEsoNet) for co-training and transfer learning from laparoscopic Sleeve Gastrectomy to the Laparoscopic part of IGS, exploring different training set compositions and training weights.
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Self-Knowledge Distillation for Surgical Phase Recognition
TL;DR: In this article , a self-knowledge distillation framework was proposed to improve the performance of SOTA models by using the teacher model to guide the training process of the student model to extract enhanced feature representations from the encoder.
References
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Journal ArticleDOI
Gene Ontology: tool for the unification of biology
M Ashburner,Catherine A. Ball,Judith A. Blake,David Botstein,Heather Butler,J. M. Cherry,Allan Peter Davis,Kara Dolinski,Selina S. Dwight,J.T. Eppig,Midori A. Harris,David P. Hill,Laurie Issel-Tarver,Andrew Kasarskis,Suzanna E. Lewis,John C. Matese,Joel E. Richardson,M. Ringwald,Gerald M. Rubin,Gavin Sherlock +19 more
TL;DR: The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing.
Journal ArticleDOI
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky,Jia Deng,Hao Su,Jonathan Krause,Sanjeev Satheesh,Sean Ma,Zhiheng Huang,Andrej Karpathy,Aditya Khosla,Michael S. Bernstein,Alexander C. Berg,Li Fei-Fei +11 more
TL;DR: The ImageNet Large Scale Visual Recognition Challenge (ILSVRC) as mentioned in this paper is a benchmark in object category classification and detection on hundreds of object categories and millions of images, which has been run annually from 2010 to present, attracting participation from more than fifty institutions.
Journal ArticleDOI
Machine learning: Trends, perspectives, and prospects
TL;DR: The adoption of data-intensive machine-learning methods can be found throughout science, technology and commerce, leading to more evidence-based decision-making across many walks of life, including health care, manufacturing, education, financial modeling, policing, and marketing.
Journal ArticleDOI
Deep Learning in Medical Image Analysis
TL;DR: This review covers computer-assisted analysis of images in the field of medical imaging and introduces the fundamentals of deep learning methods and their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on.
Journal ArticleDOI
An estimation of the global volume of surgery: a modelling strategy based on available data
Thomas G. Weiser,Thomas G. Weiser,Scott E. Regenbogen,Katherine D. Thompson,Alex B. Haynes,Stuart R. Lipsitz,William R. Berry,Atul A. Gawande,Atul A. Gawande +8 more
TL;DR: In view of the high death and complication rates of major surgical procedures, surgical safety should now be a substantial global public-health concern.