Stent Deployment Detection Using Radio Frequency‐Based Sensor and Convolutional Neural Networks-Reference-Cited by-同舟云学术

Stent Deployment Detection Using Radio Frequency‐Based Sensor and Convolutional Neural Networks

Published:2020-07-20 Issue:10 Volume:2 Page:2000092
ISSN:2640-4567
Container-title:Advanced Intelligent Systems
language:en
Short-container-title:Advanced Intelligent Systems

Author:

Xu Mengya¹²,Seenivasan Lalithkumar¹,Yeo Leonard Leong Litt³,Ren Hongliang¹²^ORCID

Affiliation:

1. Department of Biomedical Engineering National University of Singapore Block E3, #03‐04, 2 Engineering Drive 3 117581 Singapore

2. National University of Singapore (Suzhou) Research Institute (NUSRI) No. 377 Linquan Street, Suzhou Industrial Park Suzhou 215123 Jiangsu P. R. China

3. Division of Neurology National University Hospital National University Health System 1E Kent Ridge Rd 119228 Singapore

Funder

Ministry of Science and Technology of the People's Republic of China

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aisy.202000092

Reference19 articles.

1. Stent implantation versus balloon angioplasty in chronic coronary occlusions: results from the GISSOC trial

2. G.Agresti S.Milani inIEEE Int. Conf. on Acoustics Speech and Signal Processing IEEE Brighton UK2019 pp.3662–3666.

3. Application of singularity expansion method for monitoring the deployment of arterial stents

4. Detection of Stent Fractures

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