Abstract: A method of building an abnormality quantifier comprising: generating at least one selected first dataset comprising measurements of a normal population or sample and at least one second selected dataset comprising measurements of an abnormal population or sample; generating an image or map by imagizing the datasets; identifying a normality zone within the image or map using the first dataset; identifying an abnormality zone within the image or map using the second dataset; determining a definition of abnormality based on a comparison of the normality zone and the abnormality zone; receiving or accessing at least one third dataset comprising measurements of a both known normal and abnormal population or sample; testing the performance of the initially defined abnormality against one or more preset performance criteria; and outputting an abnormality quantifier when optimal performance has been reached.

Abstract: A method of building an abnormality quantifier comprising: generating at least one selected first dataset comprising measurements of a normal population or sample and at least one second selected dataset comprising measurements of an abnormal population or sample; generating an image or map by imagizing the datasets; identifying a normality zone within the image or map using the first dataset; identifying an abnormality zone within the image or map using the second dataset; determining a definition of abnormality based on a comparison of the normality zone and the abnormality zone; receiving or accessing at least one third dataset comprising measurements of a both known normal and abnormal population or sample; testing the performance of the initially defined abnormality against one or more preset performance criteria; and outputting an abnormality quantifier when optimal performance has been reached.

Abstract: A system and method for classifying a structure or material in an image of a subject. The system comprises: a segmenter configured to form one or more segmentations of a structure or material in an image and generate from the segmentations one or more segmentation maps of the image including categorizations of pixels or voxels of the segmentation maps assigned from one or more respective predefined sets of categories; a classifier that implements a classification machine learning model configured to generate, based on the segmentations maps, one or more classifications and to assign to the classifications respective scores indicative of a likelihood that the structure or material, or the subject, falls into the respective classifications; and an output for outputting a result indicative of the classifications and scores.

Abstract: A computer-implemented method and system for selecting one or more regions of interest (ROIs) in an image. The method comprises: identifying one or more objects of interest that have been segmented from the image; identifying predefined landmarks of the objects; determining reference morphometrics pertaining to the objects by performing morphometrics on the objects by reference to the landmarks; selecting one or more ROIs from the objects according to the reference morphometrics, comprises identifying the location of the ROIs relative to the reference morphometrics; and outputting the selected one or more ROIs.

Abstract: A computer-implemented image analysis method and system. The method comprises: quantifying one or more features segmented and identified from a medical image of a subject; extracting clinically relevant features from non-image data pertaining to the subject; assessing the features segmented from the medical image and the features extracted from the non-image data with a trained machine learning model; and outputting one or more results of the assessing of the features.

Abstract: A computer-implemented method and system for assigning colours to an image or part thereof. The method comprises: segmenting a cluster of pixels or voxels by pixel or voxel value within the image or part thereof; and (a) highlighting features within the image or part thereof, or (b) obscuring or masking details in the image or part thereof, comprising: assigning a colour to each pixel or voxel in the image or part thereof having a pixel or voxel value in the cluster of pixels or voxels.

Abstract: A method and system for assigning colours to an image or part thereof, the method comprising: selecting a sequence of colours for assignment to the image or part thereof; determining a minimum intensity IMIN within the image or part thereof; determining a maximum intensity IMAX within the image or part thereof; and determining relative intensity values RIV(i) for each pixel or voxel i according to; (I) where I(i) is an intensity of pixel or voxel I, and f is a preselected function (such as to re-arrange the normalized values); and assigning colours to at least some pixels in the image or part thereof based on the relative intensity values and an order of each of the colours in the sequence.

Abstract: A computer-implemented method for identifying a gap between objects in an image, the method comprising: detecting contours of the objects in the image or in a binarized version thereof; locating at least one path or gap between the objects, in the image or in an intersection region being a portion of the image containing at least respective portions of the objects by: determining representative attenuations or densities of respective one or more rows and columns of the image or of the intersection region, identifying first pixels, being pixels in a column that has a representative attenuation or density of 0, and second pixels, being pixels in a row that has a representative attenuation or density of 0, determining whether there exists a path or gap between two or more boundaries by identifying at least one first or second pixel on each of two or more of the boundaries, and detecting one or more paths between the at least two boundaries; and outputting a result indicative of one or more detected paths.

Abstract: A method for analyzing a sample comprising a first material and a second material of generally different densities and having a junction therebetween, the method comprising defining a region of interest in a cross sectional image of at least a portion of the sample that includes said junction, determining a density profile of the sample within the region of interest and crossing the junction, determining a representative density of said second material, and analyzing said sample using said junction used to distinguish said first and second materials.

Abstract: A method and system for assigning colours to an image or part thereof, the method comprising: selecting a sequence of colours for assignment to the image or part thereof; determining a minimum intensity IMIN within the image or part thereof; determining a maximum intensity IMAX within the image or part thereof; and determining relative intensity values RIV(i) for each pixel or voxel i according to; (I) where I(i) is an intensity of pixel or voxel I, and f is a preselected function (such as to re-arrange the normalized values); and assigning colours to at least some pixels in the image or part thereof based on the relative intensity values and an order of each of the colours in the sequence.

Abstract: A method and system for assigning colors to an image or part thereof, the method comprising: selecting a sequence of colors for assignment to the image or part thereof; determining a minimum intensity IMIN within the image or part thereof; determining a maximum intensity IMAX within the image or part thereof; and determining relative intensity values RIV(i) for each pixel or voxel i according to; (I) where I(i) is an intensity of pixel or voxel /, and ƒ is a preselected function (such as to re-arrange the normalized values); and assigning colors to at least some pixels in the image or part thereof based on the relative intensity values and an order of each of the colors in the sequence.

Abstract: A method for quantifying the effects of a treatment of a subject, comprising: analyzing a sample of the subject, the sample comprising a material of interest and at least one adjacent material that is generally adjacent to the material of interest, the material of interest having a generally different density from the adjacent material.

Abstract: A computer-implemented system and method for analyzing a sample comprising a material of interest and at least first and second adjacent materials each generally adjacent to the material of interest, the material of interest having a generally different density from the at least first and second adjacent materials.

Abstract: A method and system for assigning colours to an image or part thereof, the method comprising: selecting a sequence of colours for assignment to the image or part thereof; determining a minimum intensity IMIN within the image or part thereof; determining a maximum intensity IMAX within the image or part thereof; and determining relative intensity values RIV(i) for each pixel or voxel i according to; (I) where I(i) is an intensity of pixel or voxel /, and ƒ is a preselected function (such as to re-arrange the normalized values); and assigning colours to at least some pixels in the image or part thereof based on the relative intensity values and an order of each of the colours in the sequence.

Abstract: A computer-implemented method for analyzing a sample comprising a first material and a second material of generally different densities and having a junction therebetween.

Abstract: A method for analyzing a sample comprising a first material and a second material of generally different densities and having a junction therebetween, the method comprising defining a region of interest in a cross sectional image of at least a portion of the sample that includes said junction, determining a density profile of the sample within the region of interest and crossing the junction, determining a representative density of said second material, and analyzing said sample using said junction used to distinguish said first and second materials.

Abstract: A method for analysing a sample comprising a first material and a second material of generally different densities and having a junction therebetween, the method comprising defining a region of interest in a cross sectional image of at least a portion of the sample that includes said junction, determining a density profile of the sample within the region of interest and crossing the junction, determining a representative density of said second material, and analysing said sample using said junction used to distinguish said first and second materials.