Systems, devices, and methods for tracking moving targets

• US 9,779,502 B1
• Filed: 02/09/2017
• Issued: 10/03/2017
• Est. Priority Date: 01/24/2013
• Status: Active Grant

• Current Assignee: KinetiCor, Inc.
• Original Assignee: KinetiCor, Inc.
• Inventors: Lovberg, John Arthur, Pan, Xiaojiang Jason
• Primary Examiner(s): Mistry, Oneal R
• Application Number:
  US15/428,495
• Publication Number:
  US 20170278237A1
• Time in Patent Office: 236 Days
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10021 Stereoscopic video; Stereoscopic image sequence
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/30168 Image quality inspection
• CPC Class Codes: G06T 2207/30196 Human being; Person
• CPC Class Codes: G06T 2207/30204 Marker
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/248 involving reference images or patches
• CPC Class Codes: G06T 7/60 Analysis of geometric attributes
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G06T 7/74 involving reference images or patches
• CPC Class Codes: H04N 23/90 Arrangement of cameras or camera modules, e.g. multiple cameras in TV studios or sports stadiums
• CPC Class Codes: H04N 7/18 Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast

Abstract

A system for tracking a moving target having up to six degrees of freedom and rapidly determining positions of the target, said system includes an easy to locate precision optical target fixed to the target. This system includes at least two cameras positioned so as to view the optical camera from different directions with each of the at least two cameras being adapted to record two dimensional images of the precision optical target defining precise target point. A computer processor is programmed to determine the target position of x, y and z and pitch, roll and yaw. In an embodiment, the system can be configured to utilize an iteration procedure whereby an approximate first-order solution is proposed and tested against the identified precise target points to determine residual errors which can be divided by the local derivatives with respect to each component of rotation and translation, to determine an iterative correction.

Claims

1. A motion compensation system for tracking and compensating for subject motion during a medical imaging scan, the motion compensation system comprising:

an optical target configured to be fixed to a subject;

at least two cameras positioned so as to view the optical target from different directions with each of the at least two cameras being configured to record two dimensional images of the optical target defining a target point, wherein the at least two cameras are attached to a head coil configured to be used in conjunction with a medical imaging scanner;

one or more computer readable storage devices configured to store a plurality of computer executable instructions; and

one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the system to determine a position of the subject, wherein the determining the position of the subject comprises;

identifying the target point and displacement of the target point based on optical images collected by the at least two cameras;

utilizing an iteration procedure, wherein the iteration procedure comprises testing an approximate first-order solution against the identified target point to determine residual errors and dividing the determined residual errors by local derivatives with respect to rotation and translation to determine an iterative correction;

repeating the iteration procedure until the residual errors are within predetermined levels of accuracy; and

utilizing the repeated iteration procedure to determine the position of the subject at rates of at least 100 times per second.

2. The motion compensation system of claim 1, wherein the at least two cameras are affixed to an exterior surface of the head coil.

3. The motion compensation system of claim 1, wherein the medical imaging scanner is a magnetic resonance scanner.

4. The motion compensation system of claim 3, further comprising the magnetic resonance scanner.

5. The motion compensation system of claim 3, wherein the determined position of the subject is utilized as an input to the magnetic resonance scanner to compensate for the subject motion.

6. The motion compensation system of claim 1, wherein the iteration procedure is a variant of the Newton-Raphson method.

7. The motion compensation system of claim 1, wherein the determined position of the subject is updated at a rate of at least 100 solutions per second with a latency of less than 10 milliseconds.

8. The motion compensation system of claim 1, wherein the determined position of the subject is updated at a rate of at least 200 solutions per second with a latency of less than 10 milliseconds.

9. The motion compensation system of claim 1, wherein the at least two cameras are embedded in the head coil.

10. The motion compensation system of claim 1, wherein the optical target comprises at least three concentric sub-targets.

11. The motion compensation system of claim 10, wherein the system is configured to calculate centroids of each sub-target by dividing a sum of a product of pixel intensity and pixel position by a sum of pixel intensity in a sub-pixel array.

12. The motion compensation system of claim 11, wherein the sub-pixel array is about 48×

48 pixels.

13. The motion compensation system of claim 10, wherein the three concentric sub-targets are each concentric ellipses.

14. A computer-implemented method for tracking and compensating for subject motion during a medical imaging scan, the computer-implemented method comprising:

attaching an optical target to a subject;

positioning at least two cameras so as to view the optical target from different directions with each of the at least two cameras being configured to record two dimensional images of the optical target defining a target point, wherein the at least two cameras are attached to a head coil configured to be used in conjunction with a medical imaging scanner; and

determining, by a computer system, a position of the subject, wherein the determining the position of the subject comprises;

identifying the target point and displacement of the target point based on optical images collected by the at least two cameras;

utilizing an iteration procedure, wherein the iteration procedure comprises testing an approximate first-order solution against the identified target point to determine residual errors and dividing the determined residual errors by local derivatives with respect to rotation and translation to determine an iterative correction;

repeating the iteration procedure until the residual errors are within predetermined levels of accuracy; and

utilizing the repeated iteration procedure to determine the position of the subject at rates of at least 100 times per second,

wherein the computer system comprises a computer processor and an electronic storage medium.

15. The computer-implemented method of claim 14, wherein the at least two cameras are affixed to an exterior surface of the head coil.

16. The computer-implemented method of claim 14, wherein the determined position of the subject is utilized as an input to the medical imaging scanner to compensate for the subject motion.

17. The computer-implemented method of claim 16, wherein the medical imaging scanner is a magnetic resonance scanner.

18. The computer-implemented method of claim 14, wherein the iteration procedure is a variant of the Newton-Raphson method.

19. The computer-implemented method of claim 14, wherein the at least two cameras are embedded in the head coil.

20. The computer-implemented method of claim 14, wherein the determined position of the subject is updated at a rate of at least 100 solutions per second with a latency of less than 10 milliseconds.