MEDICAL IMAGING AND EFFICIENT SHARING OF MEDICAL IMAGING INFORMATION

1 . A method of operation for use with a magnetic resonance imaging (MRI) based medical imaging system to automatically correct phase aliasing, the method comprising:

receiving, by at least one processor, a set of MRI data representative of an anatomical structure, the set of MRI data comprising respective anatomical structure and velocity for each of a plurality of voxels;

for each of at least some of the plurality of voxels, identifying, by the at least one processor, sharp gradients in flow velocity near a velocity encoding parameter;

connecting, by the at least one processor, all of the voxels identified as having a sharp gradient to define an enclosed boundary;

determining, by the at least one processor, whether all of the voxels in the enclosed boundary are aliased; and

responsive to determining that all of the voxels in the enclosed boundary are aliased:

adding, by the at least one processor, a multiple of the velocity encoding parameter to the velocity for each of the voxels in the enclosed boundary; or

subtracting, by the at least one processor, a multiple of the velocity encoding parameter to the velocity for each of the voxels in the enclosed boundary.

2 . The method of claim 1 , further comprising:

responsive to determining that not all of the voxels in the enclosed boundary are aliased, analyzing, by the at least one processor, the respective velocities of neighboring voxels in the enclosed boundary; and

modifying, by the at least one processor, the velocity of each of the voxels in the enclosed boundary based at least in part on the analyzed respective velocities of the neighboring voxels.

3 . The method of claim 2 wherein modifying the velocity of each of the voxels in the enclosed boundary comprises modifying the velocity of each of the voxels by an amount determined to minimize the discontinuity across the neighboring voxels.

4 . The method of claim 1 wherein determining whether all of the voxels in the enclosed boundary are aliased comprises determining whether there are any sharp gradients between neighboring voxels in the enclosed boundary.

5 . A method of operation for use with a magnetic resonance imaging (MRI) based medical imaging system, the method comprising:

receiving, by at least one processor, a set of MRI data representative of an anatomical structure, the set of MRI data comprising respective anatomical structure and velocity information for each of a plurality of voxels;

defining, by the at least one processor, a volume within the anatomical structure;

minimizing, by the at least one processor, a divergence of a velocity field for at least some of the plurality of voxels that represent the volume within the anatomical structure; and

correcting, by the at least one processor, velocity information for the at least some of the plurality of voxels which represent the volume within the anatomical structure based at least in part on the minimized divergence of the velocity field.

6 . The method of claim 5 wherein correcting velocity information for the at least some of the plurality of voxels comprises correcting x velocity, y velocity and z velocity for the at least some of the plurality of voxels.

7 . The method of claim 5 wherein minimizing a divergence of a velocity field comprises constructing a least squares divergence free approximation of the velocity field with a constraint of minimizing the divergence.

8 . The method of claim 7 wherein minimizing a divergence of a velocity field comprises iteratively minimizing a residual divergence of the velocity field.

9 . A method of operation for use with a magnetic resonance imaging (MRI) based medical imaging system to automatically correct phase aliasing, the method comprising:

receiving, by at least one processor, a set of MRI data representative of an anatomical structure, the set of MRI data comprising respective anatomical structure and velocity information for each of a plurality of voxels;

analyzing, by the at least one processor, the set of MRI data to identify a time point which corresponds to a peak diastole of a cardiac cycle;

analyzing, by the at least one processor, a variation of the velocity of at least some of the plurality of voxels over at least a portion of the cardiac cycle; and

correcting, by the at least one processor, errors in the velocity of the at least some of the plurality of voxels based at least in part on the analysis of the variation of the velocity of at least some of the plurality of voxels over at least a portion of a cardiac cycle.

10 . The method of claim 9 wherein analyzing a variation of the velocity of at least some of the plurality of voxels and correcting errors in the velocity of at least some of the plurality of voxels comprise:

for each of the at least some of the plurality of voxels,

tracking, by the at least one processor, a change in velocity between successive time points in the cardiac cycle;

determining, by the at least one processor, that aliasing has occurred if the velocity varies by more than a magnitude of a velocity encoding parameter;

responsive to determining that aliasing has occurred,

incrementing, by the at least one processor, a wrap count if the velocity was reduced by more than the velocity encoding parameter; or

decrementing, by the at least one processor, a wrap count if the velocity was increased by more than the velocity encoding parameter; and

for each point in time, modifying, by the at least one processor, the velocity based at least in part on the accumulated wrap count for the voxel.

11 . The method of claim 10 wherein modifying the velocity based at least in part on the accumulated wrap count for the voxel comprises increasing the velocity by an amount equal to product of the accumulated wrap count and two times the velocity encoding parameter.

12 . The method of claim 10 , further comprising:

determining, by the at least one processor, whether the accumulated wrap count is zero over a cardiac cycle; and

responsive to determining that the accumulated wrap count is not zero over a cardiac cycle, generating, by the at least one processor, an error signal.

13 . The method of claim 12 , further comprising:

tracking, by the at least one processor, the number of voxels for which the accumulated wrap count is not zero over a cardiac cycle.

14 . The method of claim 12 , further comprising:

correcting, by the at least one processor, errors in the velocity only for voxels for which the accumulated wrap count is not zero over a cardiac cycle.

15 . The method of claim 9 , further comprising:

identifying, by the at least one processor, which of the plurality of voxels are likely to represent blood flow; and

selecting, by the at least one processor, the at least some of the plurality of voxels for analysis based at least in part on the identification of which of the plurality of voxels are likely to represent blood flow.

16 . A method of operation for use with a magnetic resonance imaging (MRI) based medical imaging system to automatically correct artifacts due to eddy currents, the method comprising:

receiving, by at least one processor, a set of MRI data representative of an anatomical structure, the set of MRI data comprising respective anatomical structure and velocity information for each of a plurality of voxels;

receiving, by the at least one processor, an indication of which of the plurality of voxels represent static tissue;

determining, by the at least one processor, at least one eddy current correction parameter based at least in part on the velocity information for the voxels which represent static tissue; and

modifying, by the at least one processor, the velocity information for the plurality of voxels based at least in part the determined at least one eddy current correction parameter.

17 . The method claim 16 wherein receiving an indication of which of the plurality of voxels represent static tissue comprises:

filtering, by the at least one processor, the MRI data to mask regions of air;

filtering, by the at least one processor, the MRI data to mask regions of blood flow; and

filtering, by the at least one processor, the MRI data to mask regions of non-static tissue.

18 . The method of claim 17 wherein filtering the MRI data to mask regions of air comprises masking regions with anatomy image values that are below a determined threshold.

19 . The method of claim 18 , further comprising:

analyzing, by the at least one processor, a histogram for anatomy image values to determine the determined threshold.

20 . The method of claim 17 , further comprising:

receiving, by the at least one processor, at least one filter parameter via a user interface communicatively coupled to the at least one processor.

21 . A method of operation for use with a magnetic resonance imaging (MRI) based medical imaging system to automatically set an orientation of a multiplanar reconstruction, the method comprising:

receiving, by at least one processor, a set of MRI data representative of an anatomical structure, the set of MRI data comprising respective anatomical structure and velocity information for each of a plurality of voxels;

presenting, by a display communicatively coupled to the at least one processor, the MRI data;

receiving, by the at least one processor, selection of a central region of blood flow;

determining, by the at least one processor, the direction of blood flow in the central region of blood flow; and

responsive to determining the direction of blood flow, adjusting, by the at least one processor, the orientation of the multiplanar reconstruction so that the multiplanar reconstruction is on a plane that is perpendicular to the determine direction of blood flow.

22 . The method of claim 21 wherein determining the direction of blood flow in the central region of blood flow comprises:

determining a time point which corresponds to peak blood flow; and

determining the direction of blood flow at the time point which corresponds to peak blood flow.

23 . A method of operation for use with a magnetic resonance imaging (MRI) based medical imaging system to automatically quantify blood flow in an anatomical volume, the method comprising:

receiving, by at least one processor, a set of MRI data representative of an anatomical structure, the set of MRI data comprising respective anatomical structure and velocity information for each of a plurality of voxels;

identifying, by the at least one processor, an anatomical volume in the set of MRI data which comprises a blood pool;

identifying, by the at least one processor, a plane on a landmark that is at least approximately perpendicular to the flow of blood in the anatomical volume;

generating, by the at least one processor, a contour defined by the intersection of the plane and the anatomical volume; and

determining, by the at least one processor, the total flow of blood through the voxels in the generated contour.

24 . The method of claim 23 wherein determining the total flow of blood through the voxels in the generated contour comprises:

for each voxel in the generated contour, determining, by the at least one processor, a dot product of a normal vector of the plane and a velocity vector of the voxel; and

summing, by the at least one processor, the determined dot products of each of the voxels in the generated contour.

25 . The method of claim 23 wherein the velocity information comprises a plurality of velocity components, and determining the total flow of blood through the voxels in the generated contour comprises:

for each velocity component, producing a velocity multiplanar reconstruction (MPR) in the plane of the generated contour, each of the velocity MPRs comprising a plurality of MPR pixels having pixel spacing at least similar to dimension of each of the voxels;

for each MPR pixel inside the generated contour, determining, by the at least one processor, a dot product of a normal vector of the plane and a velocity vector composed of the pixel values from the generated velocity MPRs; and

summing, by the at least one processor, the determined dot products of each of the MPR pixels in the generated contour.

26 . A method of operation for use with a medical imaging system to automatically determine a volume of a particular region, the method comprising:

receiving, by at least one processor, a set of image data representative of an anatomical structure, the set of image data comprising respective anatomical structure information for each of a plurality of voxels;

receiving, by the at least one processor, an indication of a primary axis of a volume of interest;

generating, by the at least one processor, a plurality of spaced-apart slice planes along the primary axis of the volume of interest;

for each of the plurality of slice planes, generating, by the at least one processor, a closed contour which defines a boundary of the volume of interest at the slice plane;

generating, by the at least one processor, a three dimensional surface which connects the contours of all of the slice planes; and

determining, by the at least one processor, the volume of the three dimensional surface.

27 . The method of claim 26 wherein the set of image data comprises respective anatomical structure information for each of a plurality of voxels at a plurality of time points, and the method comprises:

for each of the plurality of time points,

generating, by the at least one processor, a plurality of spaced-apart slice planes along the primary axis of the volume of interest;

for each of the plurality of slice planes, generating, by the at least one processor, a closed contour which defines a boundary of the volume of interest at the slice plane;

generating, by the at least one processor, a three dimensional surface which connects the contours of all of the slice planes; and

determining, by the at least one processor, the volume of the three dimensional surface.

28 . The method of claim 26 wherein receiving an indication of a primary axis comprises receiving an indication of a primary axis that comprises one of a straight axis or a curved axis.

29 . The method of claim 26 wherein the set of image data comprises respective anatomical structure information for each of a plurality of voxels at a plurality of time points, and the primary axis comprises a primary axis that moves over at least some of the plurality of time points.

30 . The method of claim 26 wherein receiving an indication of a primary axis comprises receiving an indication of multiple axes.

31 . A method of operation for use with a medical imaging system to automatically generate a connected mask, the method comprising:

receiving, by at least one processor, a set of image data representative of an anatomical structure, the set of image data comprising respective anatomical structure information for each of a plurality of locations in space;

identifying, by the at least one processor, a seed location;

identifying, by the at least one processor, an intensity value for the seed location; and

traversing, by the at least one processor, outward from the seed location to other locations to flood fill the connected mask according to flood fill criteria, the flood fill criteria including at least whether the intensity value of the each of the locations is within a specified threshold of the intensity value for the seed location.

32 . The method of claim 31 wherein the received set of image data comprises three dimensional image data, the method further comprising:

generating, by the at least one processor, a two dimensional multiplanar reconstruction from the received image data.

33 . The method of claim 31 wherein moving outward from the seed location to other locations to flood fill the mask comprises moving outward from the seed location to other locations to flood fill the mask according to flood fill criteria which includes connectivity criteria.

34 . The method of claim 31 wherein moving outward from the seed location to other locations to flood fill the mask comprises moving outward from the seed location to other locations to flood fill the mask according to flood fill criteria, the flood fill criteria including at least one of a radius constraint or a number of flood fill steps constraint.

35 . The method of claim 31 , further comprising:

generating, by the at least one processor, a contour defined by a border of the connected mask; and

generating, by the at least one processor, an approximation contour which is an approximation of the generated contour based at least in part on the generated contour.

36 . The method of claim 35 wherein generating an approximation contour comprises generating an approximation contour using a spline which places control points at areas of high curvature.

37 . The method of claim 35 , further comprising:

dilating, by the at least one processor, the approximation contour by a determined dilation factor to generated a dilated approximation contour.

38 . A method of operation for use with a medical imaging system, the method comprising:

receiving, by at least one processor, a set of image data representative of an anatomical structure, the set of image data comprising respective anatomical structure information for each of a plurality of locations in three dimensional space;

tracking, by the at least one processor, the position and orientation of the anatomical structure at a plurality of time points;

at each of the plurality of time points, generating, by the at least one processor, a contour for the anatomical structure; and

determining, by the at least one processor, a measurement associated with the anatomical structure using the generated contours.

39 . The method of claim 38 wherein determining a measurement associated with the anatomical structure using the generated contours comprises accounting for movement of the anatomical structure over at least some of the plurality of time points.

40 . The method of claim 39 wherein accounting for movement of the anatomical structure comprises accounting for the linear and angular velocity of the anatomical structure over the at least some of the plurality of time points.

41 . The method of claim 38 wherein determining a measurement associated with the anatomical structure using the generated contours comprises determining flow through the anatomical structure.

42 . The method of claim 38 , further comprising:

presenting, by the at least one processor, a multiplanar reconstruction of the anatomical structure on a display at a plurality of time points, wherein the position and orientation of the multiplanar reconstruction tracks the generated contours over the plurality of time points.

43 . The method of claim 38 , further comprising:

presenting, by the at least one processor, a multiplanar reconstruction of the anatomical structure on a display; and

presenting, by the at least one processor, the generated contours as semi-transparent if the multiplanar reconstruction is out of plane with the generated contours.

44 . A processor-based device having at least one processor and at least one nontransitory processor-readable medium communicatively coupled to the at least one processor, and operable to perform any of the methods of claims 1 through 43 .