CataNet: Predicting remaining cataract surgery duration
| Autor: | Martin S. Zinkernagel, Raphael Sznitman, Mathias Gallardo, Sebastian Wolf, Michel Hayoz, Andrés Marafioti, Pablo Marquez Neila |
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| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Patient throughput business.industry Computer Vision and Pattern Recognition (cs.CV) medicine.medical_treatment Image and Video Processing (eess.IV) Computer Science - Computer Vision and Pattern Recognition Context (language use) Electrical Engineering and Systems Science - Image and Video Processing Cataract surgery Extractor FOS: Electrical engineering electronic engineering information engineering medicine Operations management Clinical care Duration (project management) business Estimation methods 610 Medicine & health |
| Zdroj: | Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 ISBN: 9783030872014 MICCAI (4) |
| DOI: | 10.48350/157018 |
| Popis: | Cataract surgery is a sight saving surgery that is performed over 10 million times each year around the world. With such a large demand, the ability to organize surgical wards and operating rooms efficiently is critical to delivery this therapy in routine clinical care. In this context, estimating the remaining surgical duration (RSD) during procedures is one way to help streamline patient throughput and workflows. To this end, we propose CataNet, a method for cataract surgeries that predicts in real time the RSD jointly with two influential elements: the surgeon's experience, and the current phase of the surgery. We compare CataNet to state-of-the-art RSD estimation methods, showing that it outperforms them even when phase and experience are not considered. We investigate this improvement and show that a significant contributor is the way we integrate the elapsed time into CataNet's feature extractor. Comment: Accepted at MICCAI 2021 |
| Databáze: | OpenAIRE |
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