Systems and methods for automated detection in magnetic resonance images

Patent metadata

Field	Value
Publication number	US-10416264-B2
Application number	US-201715820073-A
Country	US
Kind code	B2
Filing date	Nov 21, 2017
Priority date	Nov 22, 2016
Publication date	Sep 17, 2019
Grant date	Sep 17, 2019

Abstract

Some aspects include a method of detecting change in degree of midline shift in a brain of a patient. The method comprises, while the patient remains positioned within the low-field magnetic resonance imaging device, acquiring first magnetic resonance (MR) image data and second MR image data of the patient's brain; providing the first and second MR data as input to a trained statistical classifier to obtain corresponding first and second output, identifying, from the first output, at least one initial location of at least one landmark associated with at least one midline structure of the patient's brain; identifying, from the second output, at least one updated location of the at least one landmark; and determining a degree of change in the midline shift using the at least one initial location of the at least one landmark and the at least one updated location of the at least one landmark.

First claim

What is claimed is:

1. A method of detecting change in degree of midline shift in a brain of a patient positioned within a low-field magnetic resonance imaging (MRI) device, the method comprising:
while the patient remains positioned within the low-field MRI device, wherein the low-field MRI device is portable and operates with a B0 field strength of less than 0.1 T:
acquiring first magnetic resonance (MR) image data of the patient's brain;
providing the first MR data as input to a trained statistical classifier to obtain corresponding first output;
acquiring second MR image data for the patient's brain subsequent to acquiring the first MR image data;
providing the second MR image data as input to the trained statistical classifier to obtain corresponding second output; and
determining a degree of change in the midline shift using the first output and the second output.

2. The method of claim 1 , wherein determining the degree of change using the first output and the second output comprises:
identifying, from the first output, at least one initial location of at least one landmark associated with at least one midline structure of the patient's brain, the identifying comprising:
identifying an initial location of an anterior attachment point of a falx cerebri;
identifying an initial location of a posterior attachment point of the falx cerebri; and
identifying an initial location of a measurement point on a septum pellucidum;

identifying, from the second output, at least one updated location of the at least one landmark associated with the at least one midline structure of the patient's brain; and
determining the degree of change in the midline shift using the at least one initial location of the at least one landmark and the at least one updated location of the at least one landmark.

3. The method of claim 2 , determining an initial amount of midline shift using the identified initial locations of the anterior attachment point of the falx cerebri, the posterior attachment point of the falx cerebri, and the measurement point on the septum pellucidum.

4. The method of claim 2 , wherein identifying, from the second output, the at least one updated location of the at least one landmark associated with the at least one midline structure of the patient's brain comprises:
identifying an updated location of the anterior attachment point of the falx cerebri;
identifying an updated location of the posterior attachment point of the falx cerebri; and
identifying an updated location of the measurement point on the septum pellucidum.

5. The method of claim 4 , wherein determining the degree of change in the midline shift is performed using the identified initial and updated locations of the anterior attachment point of the falx cerebri, the posterior attachment point of the falx cerebri, and the measurement point on the septum pellucidum.

6. The method of claim 5 , wherein determining the degree of change in the midline shift comprises:
determining an initial amount of midline shift using the identified initial locations of the anterior attachment point of the falx cerebri, the posterior attachment point of the falx cerebri, and the measurement point on the septum pellucidum;
determining an updated amount of midline shift using the identified updated locations of the anterior attachment point of the falx cerebri, the posterior attachment point of the falx cerebri, and the measurement point on the septum pellucidum; and
determining the degree of change in the midline shift using the determined initial and updated amounts of midline shift.

7. The method of claim 1 , wherein the trained statistical classifier comprises a multi-layer neural network.

8. The method of claim 1 , wherein the trained statistical classifier comprises a convolutional neural network.

9. The method of claim 1 , wherein the trained statistical classifier comprises a fully convolutional neural network.

10. The method of claim 1 , wherein the trained statistical classifier comprises a convolutional neural network and a recurrent neural network.

11. The method of claim 10 , wherein the recurrent neural network comprises a long short-term memory neural network.

12. The method of claim 1 , wherein the second MR image data is obtained within one hour of the first MR image data.

13. The method of claim 1 , further comprising repeating acquiring MR image data to obtain a sequence of frames of MR image data.

14. The method of claim 13 , wherein the sequence of frames is acquired over a period of time greater than an hour while the patient remains positioned within the low-field magnetic resonance imaging device.

15. The method of claim 13 , wherein the sequence of frames is acquired over a period of time greater than two hours while the patient remains positioned within the low-field magnetic resonance imaging device.

16. The method of claim 13 , wherein the sequence of frames is acquired over a period of time greater than five hours while the patient remains positioned within the low-field magnetic resonance imaging device.

17. A low-field magnetic resonance imaging device configured to detect change in degree of midline shift in a brain of a patient positioned within a low-field magnetic resonance imaging (MRI) device, the low-field MRI device comprising:
a plurality of magnetic components, including:
a B0 magnet configured to produce, at least in part, a B0 magnetic field, wherein the low-field MRI device is portable and operates with a B0 field strength of less than 0.1 T;
at least one gradient magnet configured to spatially encode magnetic resonance data; and
at least one radio frequency coil configured to stimulate a magnetic resonance response and detect magnetic components configured to, when operated, acquire magnetic resonance image data; and

at least one controller configured to operate the plurality of magnet components to, while the patient remains positioned within the low-field magnetic resonance device, acquire first magnetic resonance (MR) image data of the patient's brain, and acquire second MR image data for the portion of the patient's brain subsequent to acquiring the first MR image data,
wherein the at least one controller further configured to perform:
providing the first and second MR data as input to a trained statistical classifier to obtain corresponding first output and second output; and
determining a degree of change in the midline shift using the first and second output.

18. At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform a method of detecting change in degree of midline shift in a brain of a patient positioned within a low-field magnetic resonance imaging (MRI) device, the method comprising:
while the patient remains positioned within the low-field MRI device, wherein the low-field MRI device is portable and operates with a B0 field strength of less than 0.1 T:
acquiring first magnetic resonance (MR) image data of the patient's brain;
providing the first MR data as input to a trained statistical classifier to obtain corresponding first output;
acquiring second MR image data of the patient's brain subsequent to acquiring the first MR image data;
providing the second MR image data as input to the trained statistical classifier to obtain corresponding second output; and
determining a degree of change in the midline shift using the first and second output.

Assignees

• Hyperfine Res Inc

Inventors

• Sofka Michal
• Rothberg Jonathan M
• Charvat Gregory L
• Ralston Tyler S

Classifications

• G16H50/70

  for mining of medical data, e.g. analysing previous cases of other patients · CPC title

• G16H30/40

  for processing medical images, e.g. editing · CPC title

• G06V10/82

  using neural networks · CPC title

• G06V10/764

  using classification, e.g. of video objects · CPC title

• G06F18/2411

  based on the proximity to a decision surface, e.g. support vector machines · CPC title