Analysis of Advanced Siamese Neural Networks for Motion Tracking of Sonography of Carotid Arteries

Mohammad Wasih, Mohamed Almekkawy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publication44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2173-2176
Number of pages4
ISBN (Electronic)9781728127828
DOIs
StatePublished - 2022
Event44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022 - Glasgow, United Kingdom
Duration: Jul 11 2022Jul 15 2022

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2022-July
ISSN (Print)1557-170X

Conference

Conference44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022
Country/TerritoryUnited Kingdom
CityGlasgow
Period7/11/227/15/22

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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