Method And System For Discriminating Image Representations Of Classes Of Objects
First Claim
Patent Images
1. A method of evaluating images of a body region, wherein at least one of the images shows an abnormality indicative of a possible lesion, comprising the steps of:
- determining locations of pixels in each image that show such abnormality;
for each of a set of intensity levels, I, determining a contour around the cluster containing the pixels at the locations determined in the step of determining;
defining a function, F, that discriminates a distinct characteristic of each contour in a nested sequence;
defining a function, G, used to characterize the changes in the value of the function F over the range of contours at each intensity level; and
identifying a lesion as being more likely to be benign or more likely to be cancerous based on at least one threshold value for the function G or based on threshold values and locations of pixels depicting a plurality of lesions within the body region.
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Abstract
A method of identifying the location of a lesion in an image and evaluating whether the identified lesion is more likely to be cancerous, benign or uncertain is provided where the image includes a plurality of pixels, each pixel having a particular intensity I in the range of 0<I<2<sup.
45 Citations
75 Claims
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1. A method of evaluating images of a body region, wherein at least one of the images shows an abnormality indicative of a possible lesion, comprising the steps of:
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determining locations of pixels in each image that show such abnormality; for each of a set of intensity levels, I, determining a contour around the cluster containing the pixels at the locations determined in the step of determining; defining a function, F, that discriminates a distinct characteristic of each contour in a nested sequence; defining a function, G, used to characterize the changes in the value of the function F over the range of contours at each intensity level; and identifying a lesion as being more likely to be benign or more likely to be cancerous based on at least one threshold value for the function G or based on threshold values and locations of pixels depicting a plurality of lesions within the body region. - View Dependent Claims (2, 3, 4, 5, 6, 73)
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7. A method of evaluating whether a lesion in an image is cancerous, benign or uncertain, the image comprising a plurality of pixels, each pixel having a particular intensity I in the range of 0≦
- I<
2N, where N is an integer>
1, comprising the steps of;defining a landmark pixel within the lesion in the image; growing a cluster around the landmark pixel which contains the lesion for each intensity value in a set of possible intensity values in the range 0 to 2N−
1;at each intensity levels in the set, constructing a region of interest such that the region of interest is a minimal polygon containing the cluster at that intensity level; computing a value of a characteristic of the minimal polygon at each of the intensity levels in the set; determining a number relating to changes in the characteristic values over the range of intensity levels; and determining whether the lesion is more likely to be cancerous, benign or uncertain in response to the number related to changes in the characteristic values over the range of intensity levels, or based on threshold values and locations of pixels depicting a plurality of lesions within the body region. - View Dependent Claims (8, 9, 10, 11, 12, 13, 74)
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14. A method of evaluating images, wherein at least one of the images contains, a lesion, over time comprising the steps of:
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gathering pixel intensities of post-images in one time frame derived from the signal captured after use of a contrast agent and pixel intensities of a pre-image derived from the signal captured before use of the contrast agent; subtracting the pixel intensities of the pre-image from the pixel intensities of the post-image to obtain pixel intensities of a subtraction image; selecting a region of interest that surrounds the lesion; setting a landmark within the region of interest, where the landmark may consist of one or more pixels; starting with level I=I(L) and decrementing I at each step, constructing the cluster of pixels that are M-connected to L, where M is an integer multiple of 2, depending on the number of dimensions reflected in the image, and have intensity level >
=I, where I(L) denotes the pixel intensity at the landmark such that the clusters form a monotonically increasing set {CN, CN−
1, . . . }, with Function(CN)<
=Function(CN−
1)<
= . . . , where Function depends in part on the number of dimensions reflected in the image, and continuing this process until intensity level equals II, where Function(CII)>
=Q, where Q is a predetermined value;determining Imin and Imax; starting with level I=lmax and decrementing through I=Imin, constructing a minimum bounding box BI around CI and computing the Functions of the boxes, BImax⊂
BImax−
1⊂
. . . , with Function(BImax)≦
Function(BImax−
1)≦
. . . ;incrementing a step counter each time that a decrement in intensity level induces a change in the Function characteristic of the minimum bounding box; outputting a total number of steps when B(J)>
B(previous bounding box); anddetermining whether the lesion is more likely to be benign, cancerous or uncertain based on the total number of steps, or based on threshold values and locations of pixels depicting a plurality of lesions within the body region. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21, 22)
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23. Software for use with a computer having a memory, an input device for generating images, and a display, the software comprising a computer usable medium having computer readable program code thereon for evaluating images, wherein at least one of the images contains a lesion, comprising:
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first program logic for determining locations of pixels in the lesion; second program logic for, for each of a set of intensity levels, I, determining a contour around the cluster containing the pixels identified in the step of determining; third program logic for defining a function, F, that discriminates a distinct characteristic of each contour in a nested sequence; fourth program logic for defining a function, G, used to characterize the changes in the value of the function F over the range of contours at each intensity level; and fifth program logic for identifying a feature responsive to the function G, as being more likely to be benign or more likely to be cancerous based on at least one threshold value for the function G, or based on threshold values and locations of pixels depicting a plurality of lesions within the body region. - View Dependent Claims (24, 25, 26, 27, 28)
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29. Software for use with a computer having a memory, an input device for generating images, and a display, the software comprising a computer usable medium having computer readable program code thereon for evaluating whether a lesion in an image is cancerous, benign or uncertain, the image comprising a plurality of pixels, each pixel having a particular intensity I in the range of 0≦
- I<
2N, where N is an integer>
1, comprising;first program logic for defining a landmark pixel within the lesion in the image; second program logic for growing a cluster around the landmark pixel which contains the lesion for each intensity value in a set of possible intensity values in the range 0 to 2N−
1;third program logic for, at each intensity level in the set, constructing a region of interest such that the region of interest is a minimal polygon containing the cluster at that intensity level; fourth program logic for computing a value of a characteristic of the minimal polygon at each of the set of intensity levels in the set; fifth program logic for determining a number related to changes in the characteristic values over the range of intensity levels; and sixth program logic for determining whether the lesion is more likely to be cancerous, benign or uncertain in response to the number related to changes in the characteristic values over the range of intensity values, or based on threshold values and locations of pixels depicting a plurality of lesions within the body region. - View Dependent Claims (30, 31, 32, 33, 34, 35)
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36. Software for use with a computer having a memory, an input device for generating images, and a display, the software comprising a computer usable medium having computer readable program code thereon for evaluating images, wherein at least one of the images contains a lesion, of at least one lesion over time comprising the steps of:
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first program logic for gathering pixel intensities of post-images in one time frame derived from the signal captured after use of a contrast agent and pixel intensities of a pre-image derived from the signal captured before use of the contrast agent; second program logic for subtracting the pixel intensities of the pre-image from the pixel intensities of the post-image to obtain pixel intensities of a subtraction image; third program logic for selecting a region of interest that surrounds the at least one lesion; fourth program logic for setting a landmark within the region of interest; fifth program logic for starting with level I=I(L) and decrementing I at each step, constructing the cluster of pixels that are M-connected to L, where M is an integer multiple of 2, depending on the number of dimensions reflected in the image, and have intensity level >
=I, where I(L) denotes the pixel intensity at the landmark such that the clusters form a monotonically increasing set {CN, CN−
1, . . . }, with Function(CN)<
=Function(CN−
1)<
= . . . , where the Function depends at least in part on the number of dimensions reflected in the image, and continuing this process until intensity level equals II, where Function(CII)>
=Q, where Q is a predetermined value;sixth program logic for determining Imax; seventh program logic for determining Imin; eighth program logic for starting with level I=Imax and decrementing through I=Imin, constructing a minimum bounding box BI around CI and computing the Functions of the boxes, BImax⊂
BImax−
1⊂
. . . , with Function(BImax)≦
Function(BImax−
1)≦
. . . ;ninth program logic for incrementing a step counter each time that a decrement in intensity level induces a change in the Function characteristic of the minimum bounding box; tenth program logic for outputting a total number of steps when B(J)>
B(previous bounding box); andeleventh program logic for determining whether the lesion is more likely to be benign, cancerous or uncertain based on the total number of steps, or based on threshold values and locations of pixels depicting a plurality of lesions within the body region. - View Dependent Claims (37, 38, 39, 40, 41, 42, 43, 44, 75)
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45. A computer program product for performing a method of evaluating images, wherein at least one of the images contains a lesion, the computer program product embodied on a computer readable memory and comprising a series of instructions for:
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determining locations of pixels in the lesion; for each of a set of intensity levels, I, determining a contour around the cluster containing the pixels identified in the step of determining; defining a function, F, that discriminates a distinct characteristic of each contour in a nested sequence; defining a function, G, used to characterize the changes in the value of the function F over the range of contours at each intensity level; and identifying a feature responsive to the function G, as being more likely to be benign or more likely to be cancerous based on at least one threshold value for the function G, or based on threshold values and locations of pixels depicting a plurality of lesions within the body region. - View Dependent Claims (46, 47, 48, 49, 50)
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51. A computer program product for performing a method of evaluating whether a lesion in an image is cancerous, benign or uncertain, the image comprising a plurality of pixels, each pixel having a particular intensity I in the range of 0≦
- I<
2N, where N is an integer>
1, the computer program product embodied on a computer readable memory and comprising a series of instructions for;defining a landmark pixel within the lesion in the image; growing a cluster around the landmark pixel which contains the lesion for each intensity value in a set of possible intensity values in the range 0 to 2N−
1;at each intensity level in the set, constructing a region of interest such that the region of interest is a minimal polygon containing the cluster at that intensity level; computing a value of a characteristic of the minimal polygon at each of the intensity levels in the set; determining a number related to changes in the characteristic values over the range of intensity levels; and determining whether the lesion is more likely to be cancerous, benign or uncertain in response to the number related to changes in the characteristic values over the range of intensity levels, or based on threshold values and locations of pixels depicting a plurality of lesions within the body region. - View Dependent Claims (52, 53, 54, 55, 56, 57)
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58. A computer program product for performing a method of evaluating images, wherein at least one of the images contains a lesion, over time, the computer program product embodied on a computer readable memory and comprising a series of instructions for:
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gathering pixel intensities of post-images in one time frame derived from the signal captured after use of a contrast agent and pixel intensities of a pre-image derived from the signal captured before use of the contrast agent; subtracting the pixel intensities of the pre-image from the pixel intensities of the post-images in one time frame to obtain pixel intensities of a subtraction image; selecting a region of interest that surrounds the lesion; setting a landmark within the region of interest; starting with level I=I(L) and decrementing I at each step, constructing the cluster of pixels that are M-connected to L, where M is an integer multiple of 2, depending on the number of dimensions reflected in the image, and have intensity level >
=I, where I(L) denotes the pixel intensity at the landmark such that the clusters form a monotonically increasing set {CN, CN−
1, . . . }, with Function(CN)<
=Function(CN−
1)<
= . . . , where the Function depends at least in part on the number of dimensions reflected in the image, and continuing this process until intensity level equals II, where Function(CII)>
=Q, where Q is predetermined value;determining Imax; determining Imin; starting with level I=Imax and decrementing through I=Imin, constructing a minimum bounding box BI around CI and computing the Functions of the boxes, BImax⊂
BImax−
1⊂
. . . , with Function(BImax)≦
Function(BImax−
1)≦
. . . ;incrementing a step counter each time that a decrement in intensity level induces a change in the Function characteristic of the minimum bounding box; outputting a total number of steps when B(J)>
B(previous bounding box); anddetermining whether the lesion is more likely to be benign, cancerous or uncertain based on the total number of steps, or based on threshold values and locations of pixels depicting a plurality of lesions within the body region. - View Dependent Claims (59, 60, 61, 62, 63, 64, 65, 66)
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67. A method of evaluating images, wherein at least one of the images contains a lesion, over time comprising the steps of:
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gathering pixel intensities of post-images in one time frame derived from the signal captured after use of a contrast agent and pixel intensities of a pre-image derived from the signal captured before use of the contrast agent; subtracting the pixel intensities of the pre-image from the pixel intensities of the post-images in one time frame to obtain pixel intensities of a subtraction image; selecting a region of interest that surrounds the lesion; setting a landmark within the region of interest; starting with level I=I(L) and decrementing I at each step, constructing the cluster of pixels that are M-connected to L, where M is an integer multiple of 2, depending on the number of dimensions reflected in the image, and have intensity level >
=I, where I(L) denotes the pixel intensity at the landmark such that the clusters form a monotonically increasing set {CN, CN−
1, . . . }, with Function(CN)<
=Function(CN−
1)<
= . . . , where Function depends in part on the number of dimensions reflected in the image, and continuing this process until intensity level equals II, where Function(CII)>
=Q, where Q is a predetermined value;starting with level J=II and decrementing by J at each step, computing a mean gradient on the border of CJ (MeanGrad(J)) using data from the post-images in one time frame where the intensity level at which MeanGrad is maximum defines level Imax; setting Imin as a highest intensity level for which the area of CImin exceeds the area of CImax multiplied by some pre-determined value, Function(CImin)>
N*Function(CImax);starting with level I=Imax and decrementing through I=Imin, constructing a minimum bounding box BI around CI and computing the Functions of the boxes, BImax⊂
BImax−
1⊂
. . . , with Function(BImax)≦
Function(BImax−
1)≦
. . . ;incrementing a step counter each time that a decrement in intensity level induces a change in the Function characteristic of the minimum bounding box; outputting a total number of steps when B(J)>
B(previous bounding box); anddetermining whether the lesion is more likely to be benign, cancerous or uncertain based on the total number of steps, or based on threshold values and locations of pixels depicting a plurality of lesions within the body region.
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68. Software for use with a computer having a memory, an input device for generating images, and a display, the software comprising a computer usable medium having computer readable program code thereon for evaluating images, wherein at least one of the images contains a lesion, over time comprising the steps of:
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first program logic for gathering pixel intensities of post-images in one time frame derived from the signal captured after use of a contrast agent and pixel intensities of a pre-image derived from the signal captured before use of the contrast agent; second program logic for subtracting the pixel intensities of the pre-image from the pixel intensities of the post-images in one time frame to obtain pixel intensities of a subtraction image; third program logic for selecting a region of interest that surrounds the lesion; fourth program logic for setting a landmark within the region of interest; fifth program logic for starting with level I=I(L) and decrementing I at each step, constructing the cluster of pixels that are M-connected to L, where M is an integer multiple of 2, depending on the number of dimensions reflected in the image, and have intensity level >
=I, where I(L) denotes the pixel intensity at the landmark such that the clusters form a monotonically increasing set {CN, CN−
1, . . . }, with Function(CN)<
=Function(CN−
1)<
= . . . , where the Function depends at least in part on the number of dimensions reflected in the image, and continuing this process until intensity level equals II, where Function(CII)>
=Q, where Q is a predetermined value;sixth program logic for starting with level J=II and decrementing by J at each step, computing a mean gradient on the border of CJ (MeanGrad(J)) using data from the post-images in one time frame where the intensity level at which MeanGrad is maximum defines level Imax; seventh program logic for setting Imin as a highest intensity level for which the area of CImin exceeds the area of CImax multiplied by some pre-determined value, Function(CImin)>
N*Function(CImax);eighth program logic for starting with level I=Imax and decrementing through I=Imin, constructing a minimum bounding box BI around CI and computing the Functions of the boxes, BImax⊂
BImax−
1⊂
. . . , with Function(BImax)≦
Function(BImax−
1)≦
. . . ;ninth program logic for incrementing a step counter each time that a decrement in intensity level induces a change in the Function characteristic of the minimum bounding box; tenth program logic for outputting a total number of steps when B(J)>
B(previous bounding box); andeleventh program logic for determining whether the lesion is more likely to be benign, cancerous or uncertain based on the total number of steps, or based on threshold values and locations of pixels depicting a plurality of lesions within the body region.
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69. A computer program product for performing a method of evaluating images, wherein at least one of the images contains a lesion, over time, the computer program product embodied on a computer readable memory and comprising a series of instructions for:
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gathering pixel intensities of post-images in one time frame derived from the signal captured after use of a contrast agent and pixel intensities of a pre-image derived from the signal captured before use of the contrast agent; subtracting the pixel intensities of the pre-image from the pixel intensities of the post-images in one time frame to obtain pixel intensities of a subtraction image; selecting a region of interest that surrounds the lesion; setting a landmark within the region of interest; starting with level I=I(L) and decrementing I at each step, constructing the cluster of pixels that are M-connected to L, where M is an integer multiple of 2, depending on the number of dimensions reflected in the image, and have intensity level >
=I, where I(L) denotes the pixel intensity at the landmark such that the clusters form a monotonically increasing set {CN, CN−
1, . . . }, with Function(CN)<
=Function(CN−
1)<
= . . . , where the Function depends at least in part on the number of dimensions reflected in the image, and continuing this process until intensity level equals II, where Function(CII)>
=Q, where Q is predetermined value;starting with level J=II and decrementing by J at each step, computing a mean gradient on the border of CJ (MeanGrad(J)) using data from the post-images in one time frame where the intensity level at which MeanGrad is maximum defines level Imax; setting Imin as a highest intensity level for which the area of CImin exceeds the area of CImax multiplied by some pre-determined value, Function(CImin)>
N*Function(CImax);starting with level I=Imax and decrementing through I=Imin, constructing a minimum bounding box BI around CI and computing the Functions of the boxes, BImax⊂
BImax−
1⊂
. . . , with Function(BImax)≦
Function(BImax−
1)≦
. . . ;incrementing a step counter each time that a decrement in intensity level induces a change in the Function characteristic of the minimum bounding box; outputting a total number of steps when B(J)>
B(previous bounding box); anddetermining whether the lesion is more likely to be benign, cancerous or uncertain based on the total number of steps, or based on threshold values and locations of pixels depicting a plurality of lesions within the body region.
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70. (canceled)
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71. (canceled)
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72. (canceled)
Specification