Automated method for tissue-based contrast media arrival detection for dynamic contrast enhanced MRI

1. A method for automated contrast arrival detection in temporally phased images or datasets of tissues comprising:

(a) identifying a plurality of tissue voxels in a plurality of temporally phased images as a function of voxel enhancement characteristics associated with discrete tissue voxels;

(b) computing with a processor average enhancement characteristics from the plurality of identified tissue voxels;

(c) comparing the average enhancement characteristics with predetermined average enhancement characteristics associated with contrast media arrival phases by operations including eliminating a current dynamic phase from consideration as the contrast arrival phase if the average signal intensity of the current dynamic phase exceeds at least one average signal intensity of a later dynamic phase relative to the current dynamic phase; and

(d) identifying contrast media arrival phases in the temporally phased images based on the comparing.

2. The method of claim 1 further comprising, establishing a plurality of candidate arrival phases and determining if an average signal enhancement curve after the candidate phase fits under a gradient line of average signal enhancement change at a first candidate arrival phase from the plurality of candidate arrival phases, and if the average signal enhancement curve does not fit, selecting a next candidate arrival phase from the plurality of candidate arrival phases.

3. The method of claim 2 wherein, if the average signal enhancement curve fits, selecting the candidate arrival phase as one of the contrast media arrival phases in at least one of the datasets.

4. The method of claim 1 further comprising storing at least one of the contrast media arrival phases in a data storage device.

5. The method of claim 4 further comprising outputting at least one of the contrast media arrival phases to an output device.

6. The method of claim 1 wherein the tissues are substantially free of arteries.

7. The method of claim 1 wherein the identifying comprises comparing voxel enhancement values of the temporally phased images with an intensity noise threshold and identifying the plurality of tissue voxels based at least on the comparing.

8. The method of claim 1 wherein the identifying comprises comparing signal intensity enhancement voxel values of the temporally phased images with a signal intensity enhancement threshold.

9. The method of claim 1 wherein the identifying comprises comparing signal intensity madness voxel values of the temporally phased images with a smoothness threshold.

10. A system for automated contrast arrival detection in temporally phased images or datasets of tissues comprising:

(a) a set identified as a plurality of tissue voxels in a plurality of temporally phased images as a function of voxel enhancement characteristics associated with discrete tissue voxels;

(b) a process that computes, with a processor, average enhancement characteristics from the plurality of identified tissue voxels; and

(c) a comparator that generates a comparison result by comparing the average enhancement characteristics with predetermined average enhancement characteristics associated with contrast media arrival phases by operations including eliminating a current dynamic phase from consideration as the contrast arrival phase if the average signal intensity of the current dynamic phase exceeds at least one average signal intensity of a later dynamic phase relative to the current dynamic phase and not eliminating the current dynamic phase from consideration as the contrast arrival phase if the average signal intensity of the current dynamic phase does not exceed at least one average signal intensity of a later dynamic phase and that identifies contrast media arrival phases in the temporally phased images based on the comparison result.