Abstract: A method for automated classification of curve patterns associated with dynamic image data of a lesion in a subject in order to determine characteristics of the lesion. The method comprising the steps of loading the image data into an electronic memory means, producing a plot of signal intensity profile, converting the signal intensity profile into a contrast enhancement profile, detecting a reference enhancement profile having a highly positive slope over an initial enhancement period followed by a decreasing profile portion, deriving signature curve types based on the reference enhancement profile, classifying an enhancement curve for each pixel in a selected ROI into one of the derived signature curve types using all available time points and displaying a grid-plot of the classified enhancement curves for all pixels in the selected ROI, wherein the overall display of curves and heterogeneity provides visual indication of the characteristics of the lesion.

Abstract: The current invention provides a method of identifying a ischemic lesion. The method includes loading perfusion imaging data into an electronic memory element and deriving perfusion maps from the perfusion imaging data, where the perfusion maps include a cerebral blood volume (CBV) map and an arterial delay time (DT) map, which utilize arterial delay and dispersion effects. Ischemic pixels are determined from the perfusion imaging data, where the DT is greater than a predetermined first threshold value and the CBV is below a second threshold value and the infarct portion of the ischemic lesion is determined, where DT is greater than a predetermined third threshold value and/or the CBV is below a forth threshold value. A cluster analysis is applied to all of the determined ischemic lesion and infarct pixels and the penumbra is then determined, where mismatch regions between the ischemic lesion and the infarct core define the penumbra.

Abstract: A method of deriving blood perfusion indices for a region of interest (ROI) of a subject, comprising the steps of administering a contrast agent to the subject during a dynamic imaging scan, converting signal intensity data from raw images of the scan into contrast agent concentration data, deriving parameters from the contrast agent concentration data using at least one transport function that accounts for delay and dispersion of the contrast agent, and calculating the blood perfusion indices from the derived parameters.

Abstract: A method of deriving blood perfusion indices for a region of interest (ROI) of a subject, comprising the steps of administering a contrast agent to the subject during a dynamic imaging scan, converting signal intensity data from raw images of the scan into contrast agent concentration data, deriving parameters from the contrast agent concentration data using at least one transport function that accounts for delay and dispersion of the contrast agent, and calculating the blood perfusion indices from the derived parameters.

Abstract: The current invention provides a method of identifying a ischemic lesion. The method includes loading perfusion imaging data into an electronic memory element and deriving perfusion maps from the perfusion imaging data, where the perfusion maps include a cerebral blood volume (CBV) map and an arterial delay time (DT) map, which utilize arterial delay and dispersion effects. Ischemic pixels are determined from the perfusion imaging data, where the DT is greater than a predetermined first threshold value and the CBV is below a second threshold value and the infarct portion of the ischemic lesion is determined, where DT is greater than a predetermined third threshold value and/or the CBV is below a forth threshold value. A cluster analysis is applied to all of the determined ischemic lesion and infarct pixels and the penumbra is then determined, where mismatch regions between the ischemic lesion and the infarct core define the penumbra.

Abstract: A method of compensating for motion artefact of a portion of a subject, wherein signal intensity data representing movement of the portion of the subject is recorded and plotted on a display means. The method includes selecting a region of interest (ROI) covering an edge of the moving portion, calculating and plotting data points representing the average signal intensity of the selected ROI at specific time instances, producing a smoothed curve representing the mean of the plotted data points. The method further includes measuring the difference between the plotted data points and the smoothed curve at particular time instances to produce a difference curve, detecting a set of critical points on the difference curve, and interpolating the detected set of critical points to form a curve of equal time intervals for subsequent processing.

Abstract: A method of compensating for motion artefact of a portion of a subject, wherein signal intensity data representing movement of the portion of the subject is recorded and plotted on a display means. The method includes selecting a region of interest (ROI) covering an edge of the moving portion, calculating and plotting data points representing the average signal intensity of the selected ROI at specific time instances, producing a smoothed curve representing the mean of the plotted data points. The method further includes measuring the difference between the plotted data points and the smoothed curve at particular time instances to produce a difference curve, detecting a set of critical points on the difference curve, and interpolating the detected set of critical points to form a curve of equal time intervals for subsequent processing.