Granted Patent B2

US 12,453,871 · App. 18/640,580 · Granted Oct 28, 2025

Inventors: Young Mo Sung (Suwon, KR); Dong Hwan Kang (Seoul, KR)

Assignees: Godius Co., Ltd.; Young Mo Sung

A61N7/02G16H40/63A61N2007/0052A61N2007/0082A61N2007/0091

Abstract

Claims (63)

1 . A method, comprising:

setting, by a processor, information for a moving trajectory, an ultrasound irradiation unit, and/or an ultrasound irradiation spot;

outputting, by the processor, a transducer control signal based on the set information;

ultrasonically irradiating, by a transducer, based on the transducer control signal, one or more points while moving following a preset moving trajectory;

scanning, by the transducer, the one or more irradiated points to obtain an image;

determining, by the processor, based on the image, whether an ultrasound irradiation area contains a remaining tumor to be treated; and

based on determining that the ultrasound irradiation area contains a remaining tumor to be treated, performing additional ultrasonic irradiation, wherein performing the additional ultrasonic irradiation is based on remaining tumor possibility information generated based on a machine learning process, wherein the remaining tumor possibility information includes an expected three-dimensional position and size of the remaining tumor to be treated.

2 . The method of claim 1 , wherein setting the information comprises:

setting, by the processor, the moving trajectory to a first ultrasound irradiation unit;

setting, by the processor, a maximum number of ultrasound irradiation units and a number of points irradiated per ultrasound irradiation unit; and

setting, by the processor, a number of pulses of irradiation per point and a spacing between the points.

3 . The method of claim 2 , wherein the first ultrasound irradiation unit is set to include 1 to 5 lines.

4 . The method of claim 2 , wherein a maximum number of points irradiated per ultrasound irradiation unit is set to be in a range of 1 to 7.

5 . The method of claim 2 , wherein the number of pulses of irradiation per point is set to be in a range of 20 to 50.

6 . The method of claim 2 , wherein the spacing between the points is set to be in a range of 1 to 5 mm.

7 . The method of claim 1 , wherein scanning the one or more irradiated points to obtain the image comprises:

transmitting, by the transducer, an ultrasonic signal to a subject and receiving, by the transducer, a reflected ultrasonic signal reflected from the subject.

8 . The method of claim 1 , wherein ultrasonically irradiating the one or more points comprises irradiating a respective point of the one or more points by focusing ultrasonic waves on the respective point.

9 . The method of claim 1 , wherein the image includes a peripheral ultrasound irradiation area peripheral to the one or more irradiated points.

10 . The method of claim 9 , wherein scanning the one or more irradiated points to obtain the image comprises:

obtaining, by the processor, a distance between the transducer and an ultrasound irradiation target;

moving, by the processor, the transducer to a periphery of the ultrasound irradiation area based on a translational movement;

aligning, by the processor, the transducer with the ultrasound irradiation target by wobbling and rotating the transducer toward the ultrasound irradiation target; and

scanning, by the transducer, the one or more irradiated points and the peripheral ultrasound irradiation area.

11 . The method of claim 1 ,

wherein performing the additional ultrasonic irradiation comprises:

moving a main body of the transducer to a position of the remaining tumor to be treated based on the remaining tumor possibility information; and

further moving and rotating the transducer.

12 . The method of claim 1 , wherein the machine learning process comprises an extreme gradient boosting technique.

13 . An apparatus, comprising:

a processor configured to:

set information for a moving trajectory, an ultrasound irradiation unit, and/or an ultrasound irradiation spot; and

output a transducer control signal based on the set information;

a transducer configured to:

ultrasonically irradiate, based on the transducer control signal, one or more points while moving following a preset moving trajectory; and

scan the one or more irradiated points to obtain an image;

wherein the processor is further configured to:

determine, based on the image, whether an ultrasound irradiation area contains a remaining tumor to be treated; and

based on determining that the ultrasound irradiation area contains a remaining tumor to be treated, control the transducer to perform additional ultrasonic irradiation, wherein performing the additional ultrasonic irradiation is based on remaining tumor possibility information generated based on a machine learning process, wherein the remaining tumor possibility information includes an expected three-dimensional position and size of the remaining tumor to be treated.

14 . The apparatus of claim 13 , wherein setting the information comprises:

setting, by the processor, the moving trajectory to a first ultrasound irradiation unit;

setting, by the processor, a maximum number of ultrasound irradiation units and a number of points irradiated per ultrasound irradiation unit; and

setting, by the processor, a number of pulses of irradiation per point and a spacing between the points.

15 . The apparatus of claim 13 , wherein scanning the one or more irradiated points to obtain the image comprises:

transmitting an ultrasonic signal to a subject and receiving a reflected ultrasonic signal reflected from the subject.

16 . The apparatus of claim 13 , wherein ultrasonically irradiating the one or more points comprises irradiating a respective point of the one or more points by focusing ultrasonic waves on the respective point.

17 . The apparatus of claim 13 , wherein the image includes a peripheral ultrasound irradiation area peripheral to the one or more irradiated points.

18 . The apparatus of claim 17 , wherein scanning the one or more irradiated points to obtain the image comprises:

obtaining a distance between the transducer and an ultrasound irradiation target;

moving the transducer to a periphery of the ultrasound irradiation area based on a translational movement;

aligning the transducer with the ultrasound irradiation target by wobbling and rotating the transducer toward the ultrasound irradiation target; and

scanning the one or more irradiated points and the peripheral ultrasound irradiation area.

19 . The apparatus of claim 13 ,

wherein performing the additional ultrasonic irradiation comprises:

moving a main body of the transducer to a position of the remaining tumor to be treated based on the remaining tumor possibility information; and

further moving and rotating the transducer.

20 . A non-transitory computer-readable medium having processor-executable instructions stored thereon, wherein the processor-executable instructions, when executed, facilitate performance of the following:

setting, by a processor, information for a moving trajectory, an ultrasound irradiation unit, and/or an ultrasound irradiation spot;

outputting, by the processor, a transducer control signal based on the set information;

ultrasonically irradiating, by a transducer, based on the transducer control signal, one or more points while moving following a preset moving trajectory;

scanning, by the transducer, the one or more irradiated points to obtain an image;

determining, by the processor, based on the image, whether an ultrasound irradiation area contains a remaining tumor to be treated; and

based on determining that the ultrasound irradiation area contains a remaining tumor to be treated, performing additional ultrasonic irradiation, wherein performing the additional ultrasonic irradiation is based on remaining tumor possibility information generated based on a machine learning process, wherein the remaining tumor possibility information includes an expected three-dimensional position and size of the remaining tumor to be treated.

Assignments (2)

Priority Claims (1)

Continuity (2)

References Cited (27)