Ultrasound Shear Wave Elasticity Imaging With Spatio-Temporal Deep Learning

被引：13

作者：

Neidhardt, Maximilian ^{[1
]}

Bengs, Marcel ^{[1
]}

Latus, Sarah ^{[1
]}

Gerlach, Stefan ^{[1
]}

Cyron, Christian J. ^{[2
]}

Sprenger, Johanna ^{[1
]}

Schlaefer, Alexander ^{[1
]}

机构：

[1] Hamburg Univ Technol, Inst Med Technol & Intelligent Syst, D-21073 Hamburg, Germany

[2] Hamburg Univ Technol, Dept Continuum & Mat Mech, Hamburg, Germany

来源：

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | 2022年 / 69卷 / 11期

关键词：

Elasticity; Phantoms; Imaging; Ultrasonic imaging; Deep learning; Three-dimensional displays; Young's modulus; Elasticity imaging; 3D deep learning; high-speed ultrasound imaging; spatio-temporal data; soft tissue; QUANTITATIVE ASSESSMENT; SPEED ESTIMATION; ELASTOGRAPHY; BREAST; INDENTER; TISSUES; MODULI;

D O I：

10.1109/TBME.2022.3168566

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Ultrasound shear wave elasticity imaging is a valuable tool for quantifying the elastic properties of tissue. Typically, the shear wave velocity is derived and mapped to an elasticity value, which neglects information such as the shape of the propagating shear wave or push sequence characteristics. We present 3D spatio-temporal CNNs for fast local elasticity estimation from ultrasound data. This approach is based on retrieving elastic properties from shear wave propagation within small local regions. A large training data set is acquired with a robot from homogeneous gelatin phantoms ranging from 17.42 kPa to 126.05 kPa with various push locations. The results show that our approach can estimate elastic properties on a pixelwise basis with a mean absolute error of 5.01(437) kPa. Furthermore, we estimate local elasticity independent of the push location and can even perform accurate estimates inside the push region. For phantoms with embedded inclusions, we report a 53.93% lower MAE (7.50 kPa) and on the background of 85.24% (1.64 kPa) compared to a conventional shear wave method. Overall, our method offers fast local estimations of elastic properties with small spatio-temporal window sizes.

引用

页码：3356 / 3364

页数：9

共 43 条

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