Multi-Modal Learning from Video, Eye Tracking, and Pupillometry for Operator Skill Characterization in Clinical Fetal Ultrasound-Reference-Cited by-同舟云学术

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Multi-Modal Learning from Video, Eye Tracking, and Pupillometry for Operator Skill Characterization in Clinical Fetal Ultrasound

Published:2021-04-13 Issue: Volume: Page:
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Container-title:2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)
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Author:

Sharma Harshita,Drukker Lior,Papageorghiou Aris T.,Noble J. Alison

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9433749/9433753/09433863.pdf?arnumber=9433863

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Systematic comparison of deep-learning based fusion strategies for multi-modal ultrasound in diagnosis of liver cancer;Neurocomputing;2024-10

2. Low-Profile 6-Axis Differential Magnetic Force/Torque Sensing;IEEE Transactions on Medical Robotics and Bionics;2024-08

3. The Use of Machine Learning in Eye Tracking Studies in Medical Imaging: A Review;IEEE Journal of Biomedical and Health Informatics;2024-06

4. Evolving the Era of 5D Ultrasound? A Systematic Literature Review on the Applications for Artificial Intelligence Ultrasound Imaging in Obstetrics and Gynecology;Journal of Clinical Medicine;2023-10-29

5. Towards Differential Magnetic Force Sensing for Ultrasound Teleoperation;2023 IEEE World Haptics Conference (WHC);2023-07-10

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