Systems and methods for ultrasound imaging

Patent metadata

Field	Value
Publication number	US-12582385-B2
Application number	US-202318401237-A
Country	US
Kind code	B2
Filing date	Dec 29, 2023
Priority date	Dec 29, 2022
Publication date	Mar 24, 2026
Grant date	Mar 24, 2026

Abstract

Systems and methods for ultrasound imaging are provided. The systems may determine a target clinical scene associated with a target subject. The systems may determine, based on a corresponding relationship between clinical scenes and ultrasound probes, at least one ultrasound probe corresponding to the target clinical scene and determine a target ultrasound probe from the at least one ultrasound probe. The systems may generate an ultrasound image of the target subject by performing the ultrasound imaging using the target ultrasound probe.

First claim

What is claimed is:

1 . A method for ultrasound imaging, implemented on a computing device including at least one processor and at least one storage device, the method comprising:
determining a target clinical scene associated with a target subject; determining, automatically by the computing device and based on a first corresponding relationship between clinical scenes and ultrasound probes, at least one ultrasound probe corresponding to the target clinical scene; determining, automatically by the computing device, a target ultrasound probe from the at least one ultrasound probe; determining, automatically by the computing device, at least one preset imaging parameter set corresponding to the target ultrasound probe based on a second corresponding relationship between ultrasound probes and imaging parameter sets; determining, automatically by the computing device, a target imaging parameter set from the at least one preset imaging parameter set; generating, automatically by the computing device, an ultrasound image of the target subject by performing the ultrasound imaging based on the target imaging parameter set using the target ultrasound probe; determining, automatically by the computing device, a target image processing parameter set corresponding to the target clinical scene based on a third corresponding relationship between the clinical scenes and image processing parameter sets, wherein each of the image processing parameter sets is a set of parameters used in a process of processing the ultrasound image; and processing, automatically by the computing device, the ultrasound image based on the target image processing parameter set.

2 . The method of claim 1 , wherein determining the target clinical scene associated with the target subject includes determining, automatically by the computing device, the target clinical scene associated with the target subject by:
obtaining, automatically by the computing device, first feature information of the target subject, the first feature information being related to the examination need and/or physical characteristics of the target subject; and determining, automatically by the computing device, the target clinical scene based on the first feature information.

3 . The method of claim 2 , wherein determining, automatically by the computing device, the target clinical scene based on the first feature information includes:
obtaining, automatically by the computing device, second feature information of an operator of the ultrasound imaging, the second feature information being related to the department and/or the preference of the operator; and determining, automatically by the computing device, the target clinical scene based on the first feature information and the second feature information.

4 . The method of claim 1 , wherein determining the target clinical scene associated with the target subject includes:
displaying multiple preset clinical scenes via a user terminal communicatively connected to the computing device; receiving, via the user terminal, a first trigger instruction for selecting one preset clinical scene from the multiple preset clinical scenes; and designating the selected preset clinical scene as the target clinical scene.

5 . The method of claim 4 , wherein
visual elements representing the multiple preset clinical scenes are displayed on the user terminal, and an arrangement of the visual elements on the user terminal is determined based on second feature information of an operator of the ultrasound imaging.

6 . The method of claim 4 , wherein
visual elements representing the multiple preset clinical scenes are displayed on the user terminal, and each of the visual elements includes an icon representing a scanning part of the corresponding preset clinical scene.

7 . The method of claim 4 , wherein
a body model representing the target subject is displayed on the user terminal, and the body model includes multiple scanning parts representing the multiple preset clinical scenes.

8 . The method of claim 4 , wherein
visual elements representing the multiple preset clinical scenes are displayed on the user terminal, and the visual elements on the user terminal are enlarged based on second feature information of an operator of the ultrasound imaging.

9 . The method of claim 1 , wherein when the at least one ultrasound probe corresponding to the target clinical scene includes multiple ultrasound probes, the determining, automatically by the computing device, a target ultrasound probe includes:
actuating one ultrasound probe among the multiple ultrasound probes; and designating the actuated ultrasound probe as the target ultrasound probe.

10 . The method of claim 9 , wherein the actuated ultrasound probe is selected based on a ranking result of the multiple ultrasound probes, and the ranking result of the multiple ultrasound probes is determined based on at least one of:
a usage frequency of each of the multiple ultrasound probes, a last usage time of each of the multiple ultrasound probes, or a fault record of each of the multiple ultrasound probes.

11 . The method of claim 9 , wherein the actuated ultrasound probe is selected from the multiple ultrasound probes based on first feature information of the target subject and/or second feature information of an operator using a first machine learning model.

12 . The method of claim 1 , wherein the each of the image processing parameter sets includes at least one of a measurement package, an annotation library, or a report template.

13 . The method of claim 12 , wherein the method further includes:
determining a target position parameter, corresponding to the target clinical scene, of an ultrasound imaging device configured to perform the ultrasound imaging based on a corresponding relationship between the clinical scenes and multiple position parameters of the ultrasound imaging device, each of the multiple position parameters includes a position or an angle of the ultrasound imaging device relative to a subject, and a position or an angle of an ultrasound probe of the ultrasound imaging device; before performing the ultrasound imaging, causing the ultrasound imaging device to move based on the target position parameter of the ultrasound imaging device.

14 . The method of claim 1 , wherein when the at least one preset imaging parameter set corresponding to the target ultrasound probe includes multiple preset imaging parameter sets, the determining, automatically by the computing device, a target imaging parameter set includes:
actuating one preset imaging parameter set among the multiple preset imaging parameter sets; and designating the actuated preset imaging parameter set as the target imaging parameter set.

15 . The method of claim 14 , wherein the actuated preset imaging parameter set is selected based on a ranking result of the multiple preset imaging parameter sets, and the ranking result of the multiple preset imaging parameter sets is determined based on at least one of:
a usage frequency of each of the multiple preset imaging parameter sets, a last usage time of each of the multiple preset imaging parameter sets, or a fault record associated with a usage of each of the multiple preset imaging parameter sets.

16 . The method of claim 14 , wherein the actuated preset imaging parameter set is selected from the multiple preset imaging parameter sets based on first feature information of the target subject and/or second feature information of an operator using a second machine learning model.

Assignees

• Wuhan United Imaging Healthcare Co Ltd

Inventors

• Wang Ruojin
• Cheng Li
• Zhu Hao

Classifications

• A61B8/54

  Control of the diagnostic device · CPC title

• A61B8/4477

  using several separate ultrasound transducers or probes · CPC title

• A61B8/465 Primary

  adapted to display user selection data, e.g. icons or menus · CPC title

• A61B8/4427

  Device being portable or laptop-like · CPC title

• A61B8/08 Primary

  Clinical applications (A61B8/02, A61B8/04, A61B8/06 take precedence) · CPC title