Patent Application: US-67667708-A

Abstract:
a plurality of brain atlases 1 , 2 , 3 are co - registered 4 , and mapped 8 to a scan of a brain . the mapping is then tested 9 to determine the presence of a stroke , and whether it is ischemic or hemorrhagic . this provides an accurate way of identifying strokes using patient data which is particularly suitable for use in an emergency situation such as the emergency department of a hospital .

Description:
referring to fig1 , the flow diagram of an embodiment of the invention is shown . the embodiment is a method which may be performed by any conventional computer system , for example a computer system having a processor which is caused to follow the method by reading operating instructions from a computer program product , such as a recording medium storing the instructions . the embodiment employs three input data sets which are respective brain atlases : an atlas of brain anatomy 1 an atlas of cerebral vasculature 2 and an atlas of blood supply territories 3 . any existing brain atlases can be used for this purpose , for instance the atlases developed in our lab [ 1 ][ 2 ][ 3 ][ 4 ]. the atlases are fully segmented and labeled , and their 3d version constructed . in a first step 4 of the embodiment , all the atlases 1 , 2 , 3 are mutually co - registered using any existing techniques , for instance the ftt approach [ 5 ]. in an alternative form of the method , the co - registration process is performed in advance , and data representing the three atlases and their co - registration is input to the computer system , for example on the computer program product mentioned above . the other input to the method is scan data 5 obtained by one or more scans of a particular patient . in a step 6 , the skull and scalp as well as any other extra - cerebral objects are removed from the scan . for this purpose , any existing method can be used , for instance that disclosed in [ 8 ] [ 10 ]. in a step 7 , the midsagittal plane is extracted from the scan . for this purpose , any existing method can be used , for instance that disclosed in [ 6 ] [ 7 ]. in an alternative form of the embodiment , which improves accuracy , particularly , for the brains with a curved interhemispheric fissure , step 7 is replaced with a step of obtaining the midsagittal lines for each slice as calculated , for example in [ 11 ]. in a step 8 , the mutually co - registered atlases obtained in step 4 are mapped into the scan . for this purpose any existing method can be used , for instance the ftt [ 5 ] or the statistical - based approach [ 9 ]. in addition , warping against ventricles can be used , particularly , for elder people with prominent vascular dilation . for ventricular extraction , the method described in [ 12 ] can be used . for atlas warping against the ventricles , the method described in [ 13 ] and [ 14 ] can be employed . the mapping between the segmented and labeled brain atlases delineate regions of interest in the scan data . any set of regions of interests with anatomical structures , vessels , and / or blood supply territories can be identified and used for analysis in the following steps of the embodiment . in a step 9 , a series of tests 91 , 92 , 93 applied to the output of step 9 , in order to make reach a view in relation to the test . the decision tree is shown in fig2 . when performing tests 91 , 92 , 93 , all regions of interest identified using the atlases , or any subset of them , are compared . the comparison can be done by comparing corresponding identified regions of interest in the left and right hemispheres individually ( i . e . one to one ) or for any group of regions of the same patient , and / or by comparing the identified regions of interest to data obtained from normal patients . the first test 91 is to determine whether the image contains asymmetry . the comparison can employ statistics of various kinds , in particular , the mean values and standard deviations ( e . g . by obtaining values for these for each hemisphere , and declaring asymmetry if they differ by more than a predetermined threshold ), as well as other standard statistical tests available in spss eg . [ 15 ]. more advanced techniques to capture asymmetry can also be applied including [ 16 ] [ 17 ] [ 18 ]. statistical testing can be combined with image processing techniques to eliminate certain unwanted features from the image . in particular , low and high intensity thresholds can be set manually eliminating certain image regions ( i . e . the ones outside the range between these thresholds ), so that ventricles and / or the skull can be removed , optionally the images may be smoothed initially by performing median or anisotropic smoothing , and then the statistical tests can applied to the intensities within the defined range [ 19 ] [ 20 ] [ 21 ] [ 22 ] [ 23 ] [ 24 ] [ 25 ][ 26 ] [ 27 ]. in principle the smoothing step can be useful even if the thresholds are not employed . the scan is considered normal if all the corresponding regions tested produce no significant difference . if any region varies significantly from that in the contralateral hemisphere ( or normal ), the scan is considered abnormal . the second test 92 is to determine whether the asymmetry is due to a stroke , or instead to some other factor . there are several situations mimicking the stroke , and additional acquisitions and human intervention may be necessary to distinguish stroke from no stroke pathology [ 28 ], [ 29 ]. sub - step 93 is discrimination between ischemic and hemorrhagic scans . this can be done based on intensity distribution [ 28 ] and [ 29 ]. in ct scans , hyperdensity signals hemorrahage , while hypointensity indicates ischemia . on t2 mr scans , this relationship is the reverse . hounsfield units ( hu ) can further be used for discrimination ; 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