ArticleComputational and mathematical methods in medicine2015
A VidEo-Based Intelligent Recognition and Decision System for the Phacoemulsification Cataract Surgery.
Article in Computational and mathematical methods in medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Artificial Intelligence in Cataract Surgery: A Systematic Review.Translational vision science & technology · 2024Pooled it
- PhacoTrainer: Deep Learning for Cataract Surgical Videos to Track Surgical Tools.Translational vision science & technology · 2023Article
- Evaluation of Artificial Intelligence-Based Intraoperative Guidance Tools for Phacoemulsification Cataract Surgery.JAMA ophthalmology · 2022Article
- Artificial intelligence: A new tool in surgeon's hand.Journal of education and health promotion · 2022Review
- Diagnosis of Chronic Obstructive Pulmonary Disease and Regulatory Mechanism of miR-149-3p on Alveolar Inflammatory Factors and Expression of Surfactant Proteins A (SP-A) and D (SP-D) on Lung Surface Mediated by Wnt Pathway.Computational intelligence and neuroscience · 2022Article
- Current applications of artificial intelligence for intraoperative decision support in surgery.Frontiers of medicine · 2020Review
- Assessment of Automated Identification of Phases in Videos of Cataract Surgery Using Machine Learning and Deep Learning Techniques.JAMA network open · 2019Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The phacoemulsification surgery is one of the most advanced surgeries to treat cataract. However, the conventional surgeries are always with low automatic level of operation and over reliance on the ability of surgeons. Alternatively, one imaginative scene is to use video processing and pattern recognition technologies to automatically detect the cataract grade and intelligently control the release of the ultrasonic energy while operating. Unlike cataract grading in the diagnosis system with static images, complicated background, unexpected noise, and varied information are always introduced in dynamic videos of the surgery. Here we develop a Video-Based Intelligent Recognitionand Decision (VeBIRD) system, which breaks new ground by providing a generic framework for automatically tracking the operation process and classifying the cataract grade in microscope videos of the phacoemulsification cataract surgery. VeBIRD comprises a robust eye (iris) detector with randomized Hough transform to precisely locate the eye in the noise background, an effective probe tracker with Tracking-Learning-Detection to thereafter track the operation probe in the dynamic process, and an intelligent decider with discriminative learning to finally recognize the cataract grade in the complicated video. Experiments with a variety of real microscope videos of phacoemulsification verify VeBIRD's effectiveness.
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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.