基于超声影像的下腔静脉自动识别与定位

Translated title of the contribution: Automated identification and localization of inferior vena cava based on ultrasound images

Jinghan Yang, Ziye Chen, Jingyuan Sun, Wen Cao, Chaoyang Lü, Shuo Li, Mingqiu Li, Pu Zhang, Jingzhou Xu, Chang Zhou, Yuxiang Yang, Fu Zhang, Qingli Li, Ruijun Guo, Jiangang Chen

Research output: Contribution to journalArticlepeer-review

Abstract

Objective To explore the automated identification and diameter measurement methods for inferior vena cava (IVC) based on clinical ultrasound images of IVC. Methods An automated identification and localization method based on topology and automatic tracking algorithm was proposed. Tracking algorithm was used for identifying and continuously locating to improve the efficiency and accuracy of measurement. Tests were conducted on 18 sets of ultrasound data collected from 18 patients in intensive care unit (ICU), with clinicians’ measurements as the gold standard. Results The recognition accuracy of the automated method was 94.44% (17/18), and the measurement error of IVC diameter was within the range of ±1.96s (s was the standard deviation). The automated method could replace the manual method. Conclusion The proposed IVC automated identification and localization algorithm based on topology and automatic tracking algorithm has high recognition success rate and IVC diameter measurement accuracy. It can assist clinicians in identifying and locating IVC, so as to improve the accuracy of IVC measurement.

Translated title of the contributionAutomated identification and localization of inferior vena cava based on ultrasound images
Original languageChinese (Traditional)
Pages (from-to)1107-1112
Number of pages6
JournalAcademic Journal of Naval Medical University
Volume45
Issue number9
DOIs
StatePublished - Sep 2024

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