  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+-4.37 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.
