Apparatus, methods and articles for four dimensional (4D) flow magnetic resonance imaging
An MRI image processing and analysis system may identify instances of structure in MRI flow data, e.g., coherency, derive contours and/or clinical markers based on the identified structures. The system may be remotely located from one or more MRI acquisition systems, and perform: perform error detection and/or correction on MRI data sets (e.g., phase error correction, phase aliasing, signal unwrapping, and/or on other artifacts); segmentation; visualization of flow (e.g., velocity, arterial versus venous flow, shunts) superimposed on anatomical structure, quantification; verification; and/or generation of patient specific 4-D flow protocols. An asynchronous command and imaging pipeline allows remote image processing and analysis in a timely and secure manner even with complicated or large 4-D flow MRI data sets.
1. A method of operation for use with magnetic resonance imaging (MIR) based medical imaging systems, the method comprising:
for a plurality of voxels of an MM image data set, grouping the voxels into a number of bins by at least one processor-based device;
reducing the number of bins via the at least one processor-based device;
for a first and a second one of the bins, determining which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow; and
assigning a first set of colors to the voxels representative of arterial blood flow and assigning a second set of colors to the voxels representative of venous blood flow, the second set of colors different than the first set of colors.
2. The method of claim 1 wherein assigning a first set of colors to the voxels representative of arterial blood flow includes assigning a single blue color to the voxels representative of arterial blood flow and wherein assigning the second set of colors to the voxels representative of venous blood flow includes assigning a single red color to the voxels representative of venous blood flow.
3. The method of claim 1 wherein determining which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow includes determining which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow based on a proximity of at least one of the voxels to a number of anatomical landmarks by the at least one processor-based device.
4. The method of claim 1 wherein determining which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow includes determining which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow based on a closet one of the voxels in each bin to a number of anatomical landmarks by the at least one processor-based device.
5. The method of claim 4 , further comprising:
autonomously identifying the anatomical landmarks by the processor-based device.
6. The method of claim 4 , further comprising:
receiving user input that identifies the anatomical landmarks by the processor-based device.
7. The method of claim 1 , further comprising:
for each of at least some of the plurality of voxels, determining whether the respective voxel is representative of blood flow before grouping the voxels into the number of bins; and
logically marking voxels which are determined to be representative of blood flow.
8. The method of claim 7 wherein determining whether the respective voxel is representative of blood flow includes autonomously determining whether the respective voxel is representative of blood flow by the at least one processor-based device.
9. The method of claim 7 wherein determining whether the respective voxel is representative of blood flow includes receiving user input indicative of whether the respective voxel is representative of blood flow by the at least one processor-based device.
10. The method of claim 7 wherein reducing the number of bins via the at least one processor-based device includes, where the voxels of one bin spatially contact the voxels of another bin over time, consolidating the voxels into one of the bins.
11. The method of claim 1 , further comprising:
determining if there are more than two bins; and
in response to determining if there are more than two bins, determining whether some of the voxels represent a potential shunt by the at least one processor-based device.
12. The method of claim 11 wherein determining whether some of the voxels represent a potential shunt by the at least one processor-based device includes identifying areas where adjacent bins are connected by a number of voxels that is less than a defined threshold number of voxels or by an area that is smaller than a defined threshold area.
13. The method of claim 11 , further comprising:
providing a visual emphasis to at least one of voxels that represent the potential shunt or areas at least proximate the potential shunt.
14. The method of claim 13 wherein providing a visual emphasis to at least one of voxels that represent the potential shunt or areas at least proximate the potential shunt includes assigning a third set of colors to the voxels that represent the potential shunt or areas at least proximate the potential shunt, the third set of colors different than both the first and the second sets of colors.
15. The method of claim 11 , further comprising:
receiving input by the at least one processor-based device, the input indicative of a human assessment of whether the voxels represent an actual shunt; and
updating a color of the voxels that represent the potential shunt based on the received the input indicative of the human assessment of whether the voxels represent an actual shunt.
16. The method of claim 1 wherein determining which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow includes:
for each of at least some of the bins,
identifying any voxels in the bin that have a coherence value above a threshold coherence value;
for any voxels in the bin that have a coherence value above the threshold coherence value, computing an angle between an average velocity over all of a plurality of time points and a vector that connects a centroid of the respective voxel with a centroid of an anatomical structure; and
computing an average angle between all voxels in the bin and the centroid of the anatomical structure.
17. The method of claim 16 wherein determining which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow further includes:
assigning the bin that has a highest average angle as representing the arterial blood flow; and
assigning the bin that has a lowest average angle as representing the venous blood flow.
18. The method of claim 17 wherein computing an angle between an average velocity over all of a plurality of time points and a vector that connects a centroid of the respective voxel with a centroid of an anatomical structure includes computing the angle between the average velocity over all of the plurality of time points and the vector that connects the centroid of the respective voxel with the centroid of a heart.
19. A processor-based device, comprising:
at least one nontransitory processor-readable storage medium storing at least one of instructions or data; and
at least one processor communicatively coupled to the at least one nontransitory processor-readable storage medium, in operation, the at least one processor:
for a plurality of voxels of an MM image data set, groups the voxels into a number of bins;
reduces the number of bins;
for a first and a second one of the bins, determines which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow; and
assigns a first set of colors to the voxels representative of arterial blood flow and assigning a second set of colors to the voxels representative of venous blood flow, the second set of colors different than the first set of colors.
20. The processor-based device of claim 19 wherein to determine which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow, the at least one processor determines which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow based on a proximity of at least one of the voxels to a number of anatomical landmarks.
21. The processor-based device of claim 19 wherein to determine which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow, the at least one processor determines which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow based on a closet one of the voxels in each bin to a number of anatomical landmarks.
22. The processor-based device of claim 21 wherein the at least one processor:
autonomously identifies the anatomical landmarks; or
receives user input that identifies the anatomical landmarks.
23. The processor-based device of claim 19 wherein the at least one processor:
for each of at least some of the plurality of voxels, determines whether the respective voxel is representative of blood flow before grouping the voxels into the number of bins; and
logically marks voxels which are determined to be representative of blood flow.
24. The processor-based device of claim 19 wherein to determine which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow, the at least one processor:
for each of at least some of the bins,
identifies any voxels in the bin that have a coherence value above a threshold coherence value;
for any voxels in the bin that have a coherence value above the threshold coherence value, computes an angle between an average velocity over all of a plurality of time points and a vector that connects a centroid of the respective voxel with a centroid of an anatomical structure; and
computes an average angle between all voxels in the bin and the centroid of the anatomical structure.
25. The processor-based device of claim 24 wherein to determine which of the first or the second ones of the bins includes voxels representative of arterial blood flow and which of the first or second one of the bins includes voxels representative of venous blood flow, the at least one processor:
assigns the bin that has a highest average angle as representing the arterial blood flow; and
assigns the bin that has a lowest average angle as representing the venous blood flow.
26. The processor-based device of claim 25 wherein to compute an angle between an average velocity over all of a plurality of time points and a vector that connects a centroid of the respective voxel with a centroid of an anatomical structure, the at least one processor computes the angle between the average velocity over all of the plurality of time points and the vector that connects the centroid of the respective voxel with the centroid of a heart.