ReviewSurgical endoscopy2018
Video content analysis of surgical procedures.
Review in Surgical endoscopy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 70 citations in OpenAlex.
- Automated triage of non-informative frames in minimally invasive surgical videos: a comparative study of domain-specific vision transformers versus general-purpose multimodal models.Surgical endoscopy · 2026Article
- End to end AI system for surgical gesture sequence recognition and clinical outcome prediction.NPJ digital medicine · 2026Article
- An Automated Video Analysis System for Retrospective Assessment and Real-Time Monitoring of Endoscopic Procedures (with Video).Bioengineering (Basel, Switzerland) · 2024Article
- Patient Information Summarization in Clinical Settings: Scoping Review.JMIR medical informatics · 2023Article
- An artificial intelligence model that automatically labels roux-en-Y gastric bypasses, a comparison to trained surgeon annotators.Surgical endoscopy · 2023Article
- Generic surgical process model for minimally invasive liver treatment methods.Scientific reports · 2022Article
- Automatic Detection Algorithm of Football Events in Videos.Computational intelligence and neuroscience · 2022Article
- Object and anatomical feature recognition in surgical video images based on a convolutional neural network.International journal of computer assisted radiology and surgery · 2021Article
- Against spatial-temporal discrepancy: contrastive learning-based network for surgical workflow recognition.International journal of computer assisted radiology and surgery · 2021Article
- Patch-based classification of gallbladder wall vascularity from laparoscopic images using deep learning.International journal of computer assisted radiology and surgery · 2021Article
- Automatic task recognition in a flexible endoscopy benchtop trainer with semi-supervised learning.International journal of computer assisted radiology and surgery · 2020Article
- Assisted phase and step annotation for surgical videos.International journal of computer assisted radiology and surgery · 2020Article
- Predicting the quality of surgical exposure using spatial and procedural features from laparoscopic videos.International journal of computer assisted radiology and surgery · 2020Article
- Sensor-based machine learning for workflow detection and as key to detect expert level in laparoscopic suturing and knot-tying.Surgical endoscopy · 2019Article
- Surgical Performance Analysis and Classification Based on Video Annotation of Laparoscopic Tasks.JSLS : Journal of the Society of Laparoendoscopic SurgeonsArticle
- Real-time surgical tool detection with multi-scale positional encoding and contrastive learning.Healthcare technology lettersArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn 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 reasons such as cognitive training, skills assessment, and workflow analysis. Methods from the major field of video content analysis and representation are increasingly applied in the surgical domain. In this paper, we review recent developments and analyze future directions in the field of content-based video analysis of surgical operations.
methodsThe review was obtained from PubMed and Google Scholar search on combinations of the following keywords: 'surgery', 'video', 'phase', 'task', 'skills', 'event', 'shot', 'analysis', 'retrieval', 'detection', 'classification', and 'recognition'. The collected articles were categorized and reviewed based on the technical goal sought, type of surgery performed, and structure of the operation.
resultsA total of 81 articles were included. The publication activity is constantly increasing; more than 50% of these articles were published in the last 3 years. Significant research has been performed for video task detection and retrieval in eye surgery. In endoscopic surgery, the research activity is more diverse: gesture/task classification, skills assessment, tool type recognition, shot/event detection and retrieval. Recent works employ deep neural networks for phase and tool recognition as well as shot detection.
conclusionsContent-based video analysis of surgical operations is a rapidly expanding field. Several future prospects for research exist including, inter alia, shot boundary detection, keyframe extraction, video summarization, pattern discovery, and video annotation. The development of publicly available benchmark datasets to evaluate and compare task-specific algorithms is essential.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.