A method of identifying ischemic lesions in a subject, by operating a computer program on perfusion imaging data input to a computer comprising: a. loading said perfusion imaging data into an electronic memory means, wherein said perfusion imaging data contains information of a contrast agent passing through a region of interest, wherein said ROI comprises tissue; b. measuring a global arterial input function (AIF g) from a normal major artery, wherein said AIF g is an intensity profile measured against time; c. measuring a tissue contrast agent curve C(t) in said tissue, wherein said C(t) is an intensity profile measured against time; d. deriving perfusion maps by deconvolution of said AIF g from said C(t) on a pixel-by-pixel basis using a delay compensated deconvolution method, wherein said perfusion maps comprise an arterial delay time map and cerebral blood volume, cerebral blood flow and mean transit time maps; e. determining ischemic lesion pixels from said perfusion maps, wherein said DT is greater than a predetermined first threshold value and said CBV is below a second threshold value; wherein step d) comprises: i. calculating a tissue impulse residue function by deconvolution of said AIF g from said C(t) using a model-free deconvolution method, wherein the maximum of the IRF appears at certain time point, Tmax; ii. looping through a series of delay time values, DTi, ranging from 0 to Tmax, wherein for each delay time value, an arterial transport function with a delay time DTi and a known relative dispersion factor is convolved with said AIF g to produce an AIFi, wherein an IRFi is calculated by deconvolution of said AIFi from said C(t) using said model-free deconvolution method, wherein the maximum of the IRFi appears at Tmax(i); iii. determining DT by the minimum DTi value which produces Tmax(i)=0; wherein the corresponding IRFi is recorded as IRFo; iv. determining CBF and CBV by the maximum and integral of said IRFo respectively, wherein MTT=CBV/CBF. a. loading said perfusion imaging data into an electronic memory means, wherein said perfusion imaging data contains information of a contrast agent passing through a region of interest, wherein said ROI comprises tissue; b. measuring a global arterial input function (AIF g) from a normal major artery, wherein said AIF g is an intensity profile measured against time; c. measuring a tissue contrast agent curve C(t) in said tissue, wherein said C(t) is an intensity profile measured against time; d. deriving perfusion maps by deconvolution of said AIF g from said C(t) on a pixel-by-pixel basis using a delay compensated deconvolution method, wherein said perfusion maps comprise an arterial delay time map and cerebral blood volume, cerebral blood flow and mean transit time maps; e. determining ischemic lesion pixels from said perfusion maps, wherein said DT is greater than a predetermined first threshold value and said CBV is below a second threshold value; i. calculating a tissue impulse residue function by deconvolution of said AIF g from said C(t) using a model-free deconvolution method, wherein the maximum of the IRF appears at certain time point, Tmax; ii. looping through a series of delay time values, DTi, ranging from 0 to Tmax, wherein for each delay time value, an arterial transport function with a delay time DTi and a known relative dispersion factor is convolved with said AIF g to produce an AIFi, wherein an IRFi is calculated by deconvolution of said AIFi from said C(t) using said model-free deconvolution method, wherein the maximum of the IRFi appears at Tmax(i); iii. determining DT by the minimum DTi value which produces Tmax(i)=0; wherein the corresponding IRFi is recorded as IRFo; iv. determining CBF and CBV by the maximum and integral of said IRFo respectively, wherein MTT=CBV/CBF.