ArticleInternational journal of computer assisted radiology and surgery2013
Automatic knowledge-based recognition of low-level tasks in ophthalmological procedures.
Article in International journal of computer assisted radiology and surgery, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.
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Who cites it
23 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial Intelligence in Cataract Surgery: A Systematic Review.Translational vision science & technology · 2024Pooled it
- A systematic review of annotation for surgical process model analysis in minimally invasive surgery based on video.Surgical endoscopy · 2023Pooled it
- Toward an interoperable, intraoperative situation recognition system via process modeling, execution, and control using the standards BPMN and CMMN.International journal of computer assisted radiology and surgery · 2024Article
- State-of-the-art of situation recognition systems for intraoperative procedures.Medical & biological engineering & computing · 2022Review
- Patch-based classification of gallbladder wall vascularity from laparoscopic images using deep learning.International journal of computer assisted radiology and surgery · 2021Article
- Assisted phase and step annotation for surgical videos.International journal of computer assisted radiology and surgery · 2020Article
- Automatic annotation of surgical activities using virtual reality environments.International journal of computer assisted radiology and surgery · 2019Article
- Knowledge transfer for surgical activity prediction.International journal of computer assisted radiology and surgery · 2018Article
- Sequential surgical signatures in micro-suturing task.International journal of computer assisted radiology and surgery · 2018Article
- Surgical skills: Can learning curves be computed from recordings of surgical activities?International journal of computer assisted radiology and surgery · 2018Article
- Video content analysis of surgical procedures.Surgical endoscopy · 2018Review
- A survey of context recognition in surgery.Medical & biological engineering & computing · 2017Review
- Surgical process modeling.Innovative surgical sciences · 2017Review
- A Dataset and Benchmarks for Segmentation and Recognition of Gestures in Robotic Surgery.IEEE transactions on bio-medical engineering · 2017Article
- Temporal clustering of surgical activities in robot-assisted surgery.International journal of computer assisted radiology and surgery · 2017Article
- Shot boundary detection in endoscopic surgery videos using a variational Bayesian framework.International journal of computer assisted radiology and surgery · 2016Article
- Toward cognitive pipelines of medical assistance algorithms.International journal of computer assisted radiology and surgery · 2016Review
- Bridging the gap between formal and experience-based knowledge for context-aware laparoscopy.International journal of computer assisted radiology and surgery · 2016Article
- LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition.International journal of computer assisted radiology and surgery · 2015Article
- Automatic phase prediction from low-level surgical activities.International journal of computer assisted radiology and surgery · 2015Article
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Authors and funding
4 authors.
Funding
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Abstract
purposeSurgical process models (SPMs) have recently been created for situation-aware computer-assisted systems in the operating room. One important challenge in this area is the automatic acquisition of SPMs. The purpose of this study is to present a new method for the automatic detection of low-level surgical tasks, that is, the sequence of activities in a surgical procedure, from microscope video images only. The level of granularity that we addressed in this work is symbolized by activities formalized by triplets <action, surgical tool, anatomical structure> .
methodsUsing the results of our latest work on the recognition of surgical phases in cataract surgeries, and based on the hypothesis that most activities occur in one or two phases only, we created a light-weight ontology, formalized as a hierarchical decomposition into phases and activities. Information concerning the surgical tools, the areas where tools are used and three other visual cues were detected through an image-based approach and combined with the information of the current surgical phase within a knowledge-based recognition system. Knowing the surgical phases before the activity, recognition allows supervised classification to be adapted to the phase. Multiclass Support Vector Machines were chosen as a classification algorithm.
resultsUsing a dataset of 20 cataract surgeries, and identifying 25 possible pairs of activities, a frame-by-frame recognition rate of 64.5 % was achieved with the proposed system.
conclusionsThe addition of human knowledge to traditional bottom-up approaches based on image analysis appears to be promising for low-level task detection. The results of this work could be used for the automatic indexation of post-operative videos.
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