[HTML][HTML] Machine learning for surgical phase recognition: a systematic review

CR Garrow, KF Kowalewski, L Li, M Wagner… - Annals of …, 2021 - journals.lww.com
Objective: To provide an overview of ML models and data streams utilized for automated
surgical phase recognition. Background: Phase recognition identifies different steps and …

Machine and deep learning for workflow recognition during surgery

N Padoy - Minimally Invasive Therapy & Allied Technologies, 2019 - Taylor & Francis
Recent years have seen tremendous progress in artificial intelligence (AI), such as with the
automatic and real-time recognition of objects and activities in videos in the field of computer …

Multi-task recurrent convolutional network with correlation loss for surgical video analysis

Y **, H Li, Q Dou, H Chen, J Qin, CW Fu… - Medical image analysis, 2020 - Elsevier
Surgical tool presence detection and surgical phase recognition are two fundamental yet
challenging tasks in surgical video analysis as well as very essential components in various …

Real-time automatic surgical phase recognition in laparoscopic sigmoidectomy using the convolutional neural network-based deep learning approach

D Kitaguchi, N Takeshita, H Matsuzaki, H Takano… - Surgical …, 2020 - Springer
Background Automatic surgical workflow recognition is a key component for develo** the
context-aware computer-assisted surgery (CA-CAS) systems. However, automatic surgical …

Impact of data on generalization of AI for surgical intelligence applications

O Bar, D Neimark, M Zohar, GD Hager, R Girshick… - Scientific reports, 2020 - nature.com
AI is becoming ubiquitous, revolutionizing many aspects of our lives. In surgery, it is still a
promise. AI has the potential to improve surgeon performance and impact patient care, from …

Video content analysis of surgical procedures

C Loukas - Surgical endoscopy, 2018 - Springer
Background In addition to its therapeutic benefits, minimally invasive surgery offers the
potential for video recording of the operation. The videos may be archived and used later for …

Prediction of laparoscopic procedure duration using unlabeled, multimodal sensor data

S Bodenstedt, M Wagner, L Mündermann… - International Journal of …, 2019 - Springer
Purpose The course of surgical procedures is often unpredictable, making it difficult to
estimate the duration of procedures beforehand. This uncertainty makes scheduling surgical …

Assisted phase and step annotation for surgical videos

G Lecuyer, M Ragot, N Martin, L Launay… - International journal of …, 2020 - Springer
Purpose Annotation of surgical videos is a time-consuming task which requires specific
knowledge. In this paper, we present and evaluate a deep learning-based method that …

Temporal coherence-based self-supervised learning for laparoscopic workflow analysis

I Funke, A Jenke, ST Mees, J Weitz, S Speidel… - … Workshop on Computer …, 2018 - Springer
In order to provide the right type of assistance at the right time, computer-assisted surgery
systems need context awareness. To achieve this, methods for surgical workflow analysis …

Unsupervised temporal context learning using convolutional neural networks for laparoscopic workflow analysis

S Bodenstedt, M Wagner, D Katić, P Mietkowski… - arxiv preprint arxiv …, 2017 - arxiv.org
Computer-assisted surgery (CAS) aims to provide the surgeon with the right type of
assistance at the right moment. Such assistance systems are especially relevant in …