The morphological characteristics of skeletal muscles, such as fascicle orientation, fascicle length, and muscle thickness, contain valuable mechanical information that aids in understanding muscle contractility and excitation due to commands from the central nervous system. Ultrasound (US) imaging, a non-invasive measurement technique, has been employed in clinical research to provide visualized images that capture morphological characteristics. However, accurately and efficiently detecting the fascicle in US images is challenging.

DOI Link: 
10.21227/23sj-wv86
Links or DOI: 
Shallow Neural Networks with Weighted Hough Transform for Muscle Fascicles Detection in Ultrasound Images
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[1] Xuefeng Bao, "Original ultrasound images and Hough transformed images", IEEE Dataport, 2023. [Online]. Available: http://dx.doi.org/10.21227/23sj-wv86. Accessed: Sep. 16, 2024.
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url = {http://dx.doi.org/10.21227/23sj-wv86},
author = {Xuefeng Bao },
publisher = {IEEE Dataport},
title = {Original ultrasound images and Hough transformed images},
year = {2023} }
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T1 - Original ultrasound images and Hough transformed images
AU - Xuefeng Bao
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Xuefeng Bao. (2023). Original ultrasound images and Hough transformed images. IEEE Dataport. http://dx.doi.org/10.21227/23sj-wv86
Xuefeng Bao, 2023. Original ultrasound images and Hough transformed images. Available at: http://dx.doi.org/10.21227/23sj-wv86.
Xuefeng Bao. (2023). "Original ultrasound images and Hough transformed images." Web.
1. Xuefeng Bao. Original ultrasound images and Hough transformed images [Internet]. IEEE Dataport; 2023. Available from : http://dx.doi.org/10.21227/23sj-wv86
Xuefeng Bao. "Original ultrasound images and Hough transformed images." doi: 10.21227/23sj-wv86