US 5,633,509 A · Energy subtraction processing method and apparatus

An energy subtraction processing method, comprising the steps of:

i) forming a plurality of radiation images of a single object respectively with a plurality of kinds of radiation having different energy distributions, the object being constituted of a plurality of tissues exhibiting different levels of radiation absorptivity with respect to the plurality of kinds of radiation having different energy distributions,
ii) obtaining a plurality of image signals respectively representing the plurality of the radiation images, each of the plurality of the image signals being made up of a series of image signal components,
iii) calculating an unsharp mask signal Lu, which corresponds to super-low frequency, from a single image signal, which is among the plurality of the image signals, or from an image signal, which represents the mean-level image of the plurality of the radiation images and is calculated from the plurality of the image signals,
iv) changing the values of parameters, which are used for a subtraction process, in accordance with the unsharp mask signal Lu, and
v) subtracting the image signal components of the plurality of the image signals from one another, which image signal components represent corresponding picture elements in the plurality of the radiation images, with the value of each of the parameters being thus changed for different picture elements in each of the plurality of the radiation images,
wherein the unsharp mask signal Lu represents the median value of the image signal values of all picture elements located within an unsharp mask, which is set in order to obtain the unsharp mask signal Lu.

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An energy subtraction processing method, comprising the steps of:

i) forming a plurality of radiation images of a single object respectively with a plurality of kinds of radiation having different energy distributions, the object being constituted of a plurality of tissues exhibiting different levels of radiation absorptivity with respect to the plurality of kinds of radiation having different energy distributions,
ii) obtaining a plurality of image signals respectively representing the plurality of the radiation images, each of the plurality of the image signals being made up of a series of image signal components,
iii) calculating an unsharp mask signal Lu, which corresponds to super-low frequency, from a single image signal, which is among the plurality of the image signals, or from an image signal, which represents the mean-level image of the plurality of the radiation images and is calculated from the plurality of the image signals,
iv) changing the values of parameters, which are used for a subtraction process, in accordance with the unsharp mask signal Lu, and
v) subtracting the image signal components of the plurality of the image signals from one another, which image signal components represent corresponding picture elements in the plurality of the radiation images, with the value of each of the parameters being thus changed for different picture elements in each of the plurality of the radiation images,
wherein the unsharp mask signal Lu represents the mean value of the image signal values of all picture elements located within a rectangular unsharp mask having shorter sides, which extend across an edge of a region of interest in the image, and longer sides extending in the direction along which said edge extends.

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An energy subtraction processing method, comprising the steps of:

i) forming a plurality of radiation images of a single object respectively with a plurality of kinds of radiation having different energy distributions, the object being constituted of a plurality of tissues exhibiting different levels of radiation absorptivity with respect to the plurality of kinds of radiation having different energy distributions,
ii) obtaining a plurality of image signals respectively representing the plurality of the radiation images, each of the plurality of the image signals being made up of a series of image signal components,
iii) calculating an unsharp mask signal Lu, which corresponds to super-low frequency, from a single image signal, which is among the plurality of the image signals, or from an image signal, which represents the mean-level image of the plurality of the radiation images and is calculated from the plurality of the image signals,
iv) changing the values of parameters, which are used for a subtraction process, in accordance with the unsharp mask signal Lu, and
v) subtracting the image signal components of the plurality of the image signals from one another, which image signal components represent corresponding picture elements in the plurality of the radiation images, with the value of each of the parameters being thus changed for different picture elements in each of the plurality of the radiation images,
wherein the unsharp mask signal Lu represents the mean value calculated from only the image signal values, which are among the image signal values of all picture elements located within an unsharp mask, that is set in order to obtain the unsharp mask signal Lu, and the differences of which from the image signal value of a middle picture element in said unsharp mask are not larger than a predetermined threshold value.

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An energy subtraction processing method, comprising the steps of:

i) forming a plurality of radiation images of a single object respectively with a plurality of kinds of radiation having different energy distributions, the object being constituted of a plurality of tissues exhibiting different levels of radiation absorptivity with respect to the plurality of kinds of radiation having different energy distributions,
ii) obtaining a plurality of image signals respectively representing the plurality of the radiation images, each of the plurality of the image signals being made up of a series of image signal components,
iii) calculating an unsharp mask signal Lu, which corresponds to super-low frequency, from a single image signal, which is among the plurality of the image signals, or from an image signal, which represents the mean-level image of the plurality of the radiation images and is calculated from the plurality of the image signals,
iv) changing the values of parameters, which are used for a subtraction process, in accordance with the unsharp mask signal Lu, and
v) subtracting the image signal components of the plurality of the image signals from one another, which image signal components represent corresponding picture elements in the plurality of the radiation images, with the value of each of the parameters being thus changed for different picture elements in each of the plurality of the radiation images,
wherein as for the image signal values, which are among the image signal values of all picture elements located within an unsharp mask, that is set in order to obtain the unsharp mask signal Lu, and the differences of which from the image signal value of a middle picture element in said unsharp mask are not larger than a predetermined threshold value, said image signal values are used directly as the image signal values for the calculation of the unsharp mask signal Lu,
as for the image signal values, which are among the image signal values of all picture elements located within said unsharp mask, and the differences of which from the image signal value of the middle picture element in said unsharp mask are larger than said predetermined threshold value, said predetermined threshold value is used as the image signal values for the calculation of the unsharp mask signal Lu, and
the mean value calculated from the image signal values for the calculation of the unsharp mask signal Lu is taken as the value of the unsharp mask signal Lu.

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An energy subtraction processing method, comprising the steps of:

i) forming a plurality of radiation images of a single object respectively with a plurality of kinds of radiation having different energy distributions, the object being constituted of a plurality of tissues exhibiting different levels of radiation absorptivity with respect to the plurality of kinds of radiation having different energy distributions,
ii) obtaining a plurality of image signals respectively representing the plurality of the radiation images, each of the plurality of the image signals being made up of a series of image signal components,
iii) carrying out a morphology operation on a single image signal Dorg, which is among the plurality of the image signals, or on an image signal Dorg, which represents the mean-level image of the plurality of the radiation images and is calculated from the plurality of the image signals, said morphology operation being carried out with Formula (1) or Formula (2) by using a structure element Bi, which is larger than a spatial fluctuation range of image signal values corresponding to an image portion representing an unnecessary tissue or noise in the image, and a scale factor .lambda., a morphology signal Dmor being obtained from said morphology operation, ##EQU5## wherein the expression X.crclbar..lambda.Y represents that .lambda. times of calculations for finding the Minkowski difference are carried out with the structure element Y on the image signal X, and the expression X.sym..lambda.Y represents that .lambda. times of calculations for finding the Minkowski sum are carried out with the structure element Y on the image signal X, ##EQU6## wherein the expression X.sym..lambda.Y represents that .lambda. times of calculations for finding the Minkowski sum are carried out with the structure element Y on the image signal X, and the expression X.crclbar..lambda.Y represents that .lambda. times of calculations for finding the Minkowski difference are carried out with the structure element Y on the image signal X,
iv) changing the values of parameters, which are used for a subtraction process, in accordance with said morphology signal Dmor having been obtained from said morphology operation, and
v) subtracting the image signal components of the plurality of the image signals from one another, which image signal components represent corresponding picture elements in the plurality of the radiation images, with the value of each of the parameters being thus changed for different picture elements in each of the plurality of the radiation images.

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