Bone surface extraction and dynamic tracking from ultrasound images by semantic segmentation

In this study, our aim is to extract bone surface of the tibial from ultrasound images by using semantic segmentation and track the feature point of the extraction during knee flexion and extension automatically for dynamic tracking of the tibial movement in the horizontal plane. Automatic dynamic t...

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Bibliographic Details
Published in2022 SICE International Symposium on Control Systems (SICE ISCS) pp. 74 - 79
Main Authors Haba, Taiga, Itami, Taku, Yoneyama, Jun
Format Conference Proceeding
LanguageEnglish
Japanese
Published The Society of Instrument and Control Engineers 08.03.2022
Subjects
Deep learning
Image segmentation
Knee
Legged locomotion
Performance evaluation
Screw-home movement
Semantic segmentation
Semantics
Tracking
Ultrasonic imaging
Ultrasound image
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Summary:In this study, our aim is to extract bone surface of the tibial from ultrasound images by using semantic segmentation and track the feature point of the extraction during knee flexion and extension automatically for dynamic tracking of the tibial movement in the horizontal plane. Automatic dynamic tracking is performed by approximating the bone surface extraction line to a cubic function curve and tracking the inflection point. The effectiveness of the proposed method is verified by analyzing the lower leg during knee flexion and extension by three healthy men in their 20s using ultrasound diagnostic device and confirming the physiological movement of screw-home movement(SHM) during knee flexion and extension movement. From the experimental results, SHM is confirmed during knee flexion and extension movements in each subject. Therefore, the proposed method of this study is effective in the dynamic tracking of the tibial bone surface.
DOI:10.23919/SICEISCS54350.2022.9754521