US 12,422,548 B2
Systems and methods for generating color doppler images from short and undersampled ensembles
Iason Zacharias Apostolakis, Cambridge, MA (US); Faik Can Meral, Mansfield, MA (US); Jun Seob Shin, Winchester, MA (US); Francois Guy Gerard Marie Vignon, Andover, MA (US); Shiying Wang, Melrose, MA (US); and Jean-Luc Francois-Marie Robert, Cambridge, MA (US)
Assigned to KONINKLIJKE PHILIPS N.V., Eindhoven (NL)
Appl. No. 18/010,008
Filed by KONINKLIJKE PHILIPS N.V., Eindhoven (NL)
PCT Filed Jun. 15, 2021, PCT No. PCT/EP2021/066014
§ 371(c)(1), (2) Date Dec. 13, 2022,
PCT Pub. No. WO2021/259694, PCT Pub. Date Dec. 30, 2021.
Claims priority of provisional application 63/042,602, filed on Jun. 23, 2020.
Prior Publication US 2023/0228873 A1, Jul. 20, 2023
Int. Cl. G01S 15/89 (2006.01); G01N 29/06 (2006.01); G01N 29/44 (2006.01)
CPC G01S 15/8988 (2013.01) [G01N 29/0654 (2013.01); G01N 29/4481 (2013.01); G01S 15/8915 (2013.01); G01S 15/8981 (2013.01); G01N 29/0609 (2013.01)] 16 Claims
OG exemplary drawing
 
1. An ultrasound imaging system comprising:
a processor configured to:
receive ultrasound signals corresponding to a first radiofrequency (RF) ensemble comprising a first length, a first pulse repetition frequency (PRF), and a first sensitivity;
estimate a second RF-ensemble from the first RF-ensemble based, at least in part, on reference ultrasound signals that correspond to at least one reference RF-ensemble comprising at least one of a second pulse repetition rate, a second length, or a second sensitivity different than the first RF-ensemble; and
generate a color Doppler image using the second RF-ensemble,
wherein the processor implements a neural network to estimate the second RF-ensemble,
wherein the neural network comprises a series of convolutional neural networks,
and further wherein the neural network further generates the color Doppler image, and wherein a first neural network of the series of convolutional neural networks receives the ultrasound signals corresponding to the RF-ensemble and provides a mean Doppler phase image and a Doppler phase as a first output, wherein a second neural network of the series of convolutional neural networks receives the first output and provides the color Doppler image as a second output.