TY - GEN
T1 - Analysis of Advanced Siamese Neural Networks for Motion Tracking of Sonography of Carotid Arteries
AU - Wasih, Mohammad
AU - Almekkawy, Mohamed
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The Siamese Tracker (ST) for tracking objects of interest in Ultrasound (US) images does not incorporate video specific cues and assumes a fixed template of the reference block. Recently, a more advanced version of ST, Correlation Filter Network (CFNet), which overcomes the problems of ST, has been used for tracking in US images. In this study, we demonstrate how the basic CFNet can be made computationally more efficient by reducing the number of layers in its feature extraction network. We further show that due to the unique architecture of the CFNet, this strategy does not affect the performance of the baseline CFNet considerably. Our methodology was evaluated on 10 random sequences from the publicly available carotid artery dataset. CFNet obtained a 35.7% improvement in the average localization error over the basic ST, thus demonstrating that it is a practical and robust tracking algorithm for tracking objects in US images.
AB - The Siamese Tracker (ST) for tracking objects of interest in Ultrasound (US) images does not incorporate video specific cues and assumes a fixed template of the reference block. Recently, a more advanced version of ST, Correlation Filter Network (CFNet), which overcomes the problems of ST, has been used for tracking in US images. In this study, we demonstrate how the basic CFNet can be made computationally more efficient by reducing the number of layers in its feature extraction network. We further show that due to the unique architecture of the CFNet, this strategy does not affect the performance of the baseline CFNet considerably. Our methodology was evaluated on 10 random sequences from the publicly available carotid artery dataset. CFNet obtained a 35.7% improvement in the average localization error over the basic ST, thus demonstrating that it is a practical and robust tracking algorithm for tracking objects in US images.
UR - http://www.scopus.com/inward/record.url?scp=85138128185&partnerID=8YFLogxK
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U2 - 10.1109/EMBC48229.2022.9871782
DO - 10.1109/EMBC48229.2022.9871782
M3 - Conference contribution
C2 - 36086192
AN - SCOPUS:85138128185
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 2173
EP - 2176
BT - 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
Y2 - 11 July 2022 through 15 July 2022
ER -