TRANSVERSE MUSCLE ULTRASOUND ANALYSIS (TRAMA): ROBUST AND ACCURATE SEGMENTATION OF MUSCLE CROSS-SECTIONAL AREA

被引:20
作者
Salvi, Massimo [1 ]
Caresio, Cristina [1 ,2 ]
Meiburger, Kristen M. [1 ]
De Santi, Bruno [1 ]
Molinari, Filippo [1 ]
Minetto, Marco Alessandro [3 ]
机构
[1] Politecn Torino, Biolab, Dept Elect & Telecommun, Corso Duca Abruzzi 24, I-10129 Turin, Italy
[2] Eindhoven Univ Technol, Dept Biomed Engn, Eindhoven, Netherlands
[3] Univ Turin, Dept Surg Sci, Div Phys Med & Rehabil, Turin, Italy
关键词
Muscle ultrasonography; Musculoskeletal ultrasound; Automatic; Segmentation; Visible cross-sectional area; THICKNESS; ULTRASONOGRAPHY; RELIABILITY; STRENGTH; IMAGES; SARCOPENIA; VALIDITY; SIZE;
D O I
10.1016/j.ultrasmedbio.2018.11.012
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Ultrasonography allows non-invasive and real time-measurement of the visible cross-sectional area (CSA) of muscles, which is a clinically relevant descriptor of muscle size. The aim of this study was to develop and validate a fully automatic method called transverse muscle ultrasound analysis (TRAMA) for segmentation of the muscle in B-mode transverse ultrasound images and measurement of muscle CSA. TRAMA was tested on a database of 200 ultrasound images of the rectus femoris, vastus lateralis, tibialis anterior and medial gastrocnemius muscles. The automatic CSA measurements were compared with manual measurements obtained by two operators. There were no statistical differences between the automatic and manual measurements of CSA of the four muscles, and TRAMA performance was comparable to intra-operator variability in terms of the Dice similarity coefficient and Hausdorff distance between the automatic and manual segmentations. Compared with manual segmentation, the Dice similarity coefficient for the proposed method was always higher than 93%; the Hausdorff distance never exceeded 4 mm, and the maximum absolute error was 62 mm(2). TRAMA is the first automated algorithm that analyzes and segments ultrasound scans of the muscle in the transverse plane. It can be adopted in future studies for automatic segmentation of muscle regions of interest to enhance and automatize a multitexture analysis of muscle structure. (C) 2018 World Federation for Ultrasound in Medicine & Biology. All rights reserved.
引用
收藏
页码:672 / 683
页数:12
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