Abstract: A method is proposed for processing a CT brain scan to identify hematoma and extract data quantifying it. The method uses anatomical, pathological and imaging knowledge comprising (i) distribution data obtained from population studies and characterizing typical intensity distributions of one or more different types of material present in brains, one of the types of material being hematoma, (ii) at least one spatial template describing the spatial layout of a brain. Based on these, the method defines a respective volume of interest for each of a number of ventricles, and extracts data characterizing hematoma in the volume(s) of interest, which need not be hematoma within the ventricles. The distribution data describes typical intensity distributions of hematoma (clots), grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF), and may be in Hounsfield Units (HU).

Abstract: A method (100) and an apparatus (200) are disclosed for registering an input image and an atlas. The atlas is warped (130) using non-rigid registration. In particular, boundary displacements of structures in the atlas are calculated (132) which register those structures with equivalent structures in the input image. The boundaries of structures in the atlas are then warped (133) according to their respective boundary displacements using topology preserving propagation of boundary points of the structures.

Abstract: An automatic technique for stroke identification, localization, quantification and prediction, has the steps of receiving a CT scan, pre-processing it to extract the brain region corresponding to a brain volume of a subject who has suffered a stroke; identifying whether a hemorrhage is present in the brain volume and if so obtaining data characterizing the hemorrhage; otherwise identifying whether an infarct is present and if so obtaining data characterizing it; analyzing the results using a brain atlas; and, using the results of the analysis, obtaining at least one predictive value characterizing a prediction about the subject.

Abstract: Creating a report from a radiological image using an electronic report template, the radiological image being an image of an anatomic region and the report template initially having empty fields includes displaying the radiological image on a screen of a workstation; providing a structural template, the structural template being a map of a reference region that corresponds to the anatomical region, t structural template identifying a plurality of anatomical landmarks each associated with corresponding landmark data; fitting the structural template with the radiological image such that the anatomical landmarks match corresponding anatomical landmarks of the radiological image; using the fitting to generate pathological data indicative of a pathology in one or more of the anatomical landmark and using the landmark data and pathological data to populate the empty field of the report template to thereby create the report.

Abstract: In a method of registering three-dimensional brain images, a reference slice for a midsagittal plane of each image is constructed. The reference slice comprises image points forming a cortical edge. Edge points are selected from these image points such that an ellipse fit to the edge points approximates the cortical edge. The reference ellipse in each image that fits the edge points is determined. The images are registered in a same coordinate system such that the reference ellipses in the images are aligned with one another.

Abstract: Medical scan data, such as brain scan data, from a plurality of patients suffering from a medical condition such as a stroke is used to construct a probabilistic atlas. A first portion of the atlas indicates, for each location, the corresponding likelihood of a medical abnormality (such as a lesion) associated with the medical condition being present at that location. A second portion of the atlas includes, for each location and each of one or more parameters, corresponding parameter data indicative of the values taken by the parameter for those patients suffering from the medical abnormality at the corresponding location. The probabilistic map can be used to extract outcome data from a scan obtained from a new subject, such as by locating a medical abnormality within the scan of the subject, and obtaining the outcome data using the corresponding locations in the probabilistic map.

Abstract: Disclosed herein are methods, computer systems and computer program products for labeling components. One method includes the step of labeling (130) with a current label all voxels that are internal to a predetermined sub-volume oriented with respect to an unlabeled voxel, and directly connected to the unmarked voxel. The labeling step is repeated for all voxels that are not internal to the predetermined sub-volume, but which are labeled with a current label. The method includes the step of incrementing the current label and may include the step of increasing a window size to a predetermined maximum. The preceding steps are repeated for remaining unlabeled object voxels.

Abstract: Methods (2900), apparatuses (3000), and computer program products for segmenting an infarct in a diffusion-weighted imaging (DWI) volume are disclosed. A Region of Interest in at least one slice of the DWI volume is selected (2912). The ROI comprises at least a portion of the slice. A threshold for a minimum size of an infarct region is selected (2916). An energy mask is convolved (2918) with that slice, and the resulting energy image is normalized (2920). The ROI in the convolved energy image is selected (2922). An initial threshold is determined (2924) using a histogram of the ROI of the slice without a background region, and an initial segmentation of the slice is performed (2926). Individual components of the initial segmentation of the slice are labeled (2930). A final threshold is determined (2932) using histograms of labeled components if the initial segmentation, and a final segmentation if the slice is performed (2934) using that threshold.

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.

Abstract: A method and apparatus for identifying pathology in a brain image comprises the steps of firstly determining the location of the midsagittal plane (MSP) of the brain illustrated in the image under examination by identifying the symmetry of the two hemispheres based on the determination of up to 16 approximated fissure line segments (AFLSs). Those AFLSs with a larger angular deviation from the MSP than a predefined threshold are considered as outlier AFLSs while the rest are taken as inlier AFLSs. The ratio of the number of the outlier AFLSs to the number of inlier AFLSs is then calculated. A comparison of the ratio with a further predetermined threshold value is made and if the ratio exceeds the further predetermined threshold value, pathology is present in the brain image.

Abstract: A method of segmenting CT scan data comprises transforming intensity data into transformed data values. In a first option, the method includes convolving the CT scan data with a mask to obtain energy data wherein the mask has band pass filter characteristics, generating a histogram of the energy data and segmenting the CT scan data based on energy values in the generated histogram. In a second option, the method includes transforming the intensity data into Hounsfield scale data, and segmenting the image based on predefined Hounsfield scale values.

Abstract: A method is proposed for segmenting one or more ventricles in a three-dimensional brain scan image (e.g. MR or CT). The image is registered against a brain model, which ventricle models of each of the one or more ventricles. Respective regions of interest are defined based on the ventricle models. Object regions are first obtained by applying region growing procedure in the regions of interest, and then trimmed based on anatomical knowledge. A 3D surface model of one or more objects is constructed within a 3D space from the segmented structure. A 3D surface is edited and refined by a user selecting amendment points in the 3D space which are indicative of missing detail features. A region of the 3D surface near the selected points is then warped towards the amendment points smoothly, and the modified patch is combined with the rest of the 3D surface yields the accurate anatomy structure model.

Abstract: An algorithm is proposed to eliminate from MRI images pixels which have been incorrectly identified as corresponding to infarct material. A first technique is to eliminate identified regions which are determined to be similar to the region of the scan which corresponds to the identified region reflected in the mid-sagittal plane (MSP) of the brain. A second technique is to eliminate regions which are determined not to have corresponding identified regions in one or more of the other scans. The combination of two techniques enhances the confidence in the decision of whether a hyperintense region is an infarct or artifact.

Abstract: Volumes of interest may be defined, within a three-dimensional brain image, for each of three orthogonal directions. Measures, which may, for example, be energy or entropy measures, are determined for slices of the volumes of interest in the three directions. The volume of interest corresponding to the sagittal direction is then identified. The slice, among the slices in the volume of interest corresponding to the identified sagittal direction, having the optical measure is used to define a first estimate of the mid-sagittal plane. The first estimate of the mid-sagittal plane may then be used to build an input to an optimization technique, which operates until a convergence criterion is satisfied, at which point a final estimate of the mid-sagittal plane may be produced.

Abstract: A method for determining asymmetry in an image such as an MR image of a brain comprises determining a symmetry plane to divide the image into a first part and a second part representative of, for example, the hemispheres of the brain. The probability distributions of voxels against intensities are determined for the first and second parts and histograms of intensities representative of the parts are generated. Compensation is made for any relative shift along a predetermined axis between the histograms. A divergence value based on a distance between the first and second histograms is then calculated and it is determined if the calculated divergence value is greater than a predetermined threshold. A divergence of greater than the predetermined threshold is indicative of asymmetry in the image that may be considered as suspicious for abnormality. There is also disclosed an apparatus for determining asymmetry in an image.

Abstract: Methods (2900), apparatuses (3000), and computer program products for segmenting an infarct in a diffusion-weighted imaging (DWI) volume are disclosed. A Region of Interest in at least one slice of the DWI volume is selected (2912). The ROI comprises at least a portion of the slice. A threshold for a minimum size of an infarct region is selected (2916). An energy mask is convolved (2918) with that slice, and the resulting energy image is normalized (2920). The ROI in the convolved energy image is selected (2922). An initial threshold is determined (2924) using a histogram of the ROI of the slice without a background region, and an initial segmentation of the slice is performed (2926). Individual components of the initial segmentation of the slice are labeled (2930). A final threshold is determined (2932) using histograms of labeled components if the initial segmentation, and a final segmentation if the slice is performed (2934) using that threshold.

Abstract: The present invention discloses a method for registering a measured MRI volume image with appropriate anatomical and blood supply territory Atlases to enable Atlas information to be mapped onto the measured MRI volume image. The disclosed arrangements provide an efficient method for mapping brain Atlas information (including gross anatomy and blood supply territories) into magnetic resonance perfusion and diffusion images.

Abstract: The AC and/or PC landmarks are identified in a midsagittal MRI image by firstly identifying structures in the brain (specifically the fornix and/or brainstem) as groups of pixels in a radiological image which have an intensity in ranges defined by one or more thresholds and which obey predefined geometrical criteria. The thresholds are varied until the predefined geometrical criteria are met. Initial estimates of the position of the AC and/or PC are derived from the identified structures. These estimates can be improved in various ways, especially by making use of axial and/or corona/radiological images in planes including, and/or proximate to, the initial estimated position of the AC and/or PC.

Abstract: A method and apparatus for extracting a cerebral ventricular system from images of one or more cerebral ventricular regions comprises defining multiple regions of interest (ROI) in the images, defining seed points within each ROI, growing images of ventricular regions while correcting for leakages into extraventricular space and connecting the ventricular regions grown.

Abstract: A method of estimating the location of the anterior and posterior commissures in a brain scan image is proposed. Firstly, a geometrical object is constructed using points on a brain scan image of an individual which are on the surface of the brain, such as an ellipse fitting the cerebral surface of a sagittal image of the mid-sagittal plane, or an adjacent sagittal plane. The locations on the MSP of the AC and PC landmarks (and optionally other landmarks) are estimated using the five parameters which define the ellipse, plus numerical values obtained in advance from statistical analysis of other individuals.