Automatic indentification of anatomical features of interest from data acquired in nuclear medicine studies and automatic positioning of scintillation cameras to carry out such studies at optimal positions

Claim 1

A method of identifying, from image data acquired in a nuclear medicine study of a patient's body, an anatomical feature of interest, comprising: conducting a nuclear medicine study and thereby acquiring an image of the feature, said image including, for each image pixel, an intensity representing a number of detected scintillation events which corresponds to the location of that pixel in the patient's body; establishing, on the basis of the feature to be identified, a scan curve and a scan direction; scanning the image with the scan curve along the scan direction and registering, for each location of the scan curve, the pixels with local intensity maxima and minima; grouping together, in accordance with their connectedness, some of such registered pixels, to form maxima line segments composed exclusively of pixels with local intensity maxima and minima line segments composed exclusively of pixels with local intensity minima; and determining which of said line segments correspond with the feature by identifying whether said line segments satisfy constraints which have been empirically determined to relate to the feature.

Claim 2

A method of identifying, from image data acquired in a nuclear medicine study of a patient's body, an anatomical feature of interest, comprising: conducting a nuclear medicine study and thereby acquiring an image of the feature, said image including, for each image pixel, an intensity representing a number of detected scintillation events which corresponds to the location of that pixel in the patient's body; establishing, on the basis of the feature to be identified, a scan curve and a scan direction; scanning the image with the scan curve along the scan direction and registering, for each location of the scan curve, the pixels with local intensity maxima and minima; grouping together, in accordance with their connectedness, some of such registered pixels, to form maxima line segments composed exclusively of pixels with local intensity maxima and minima line segments composed exclusively of pixels with local intensity minima; and determining which of said line segments correspond with the feature by identifying whether said line segments satisfy constraints which have been empirically determined to relate to the feature.

Claim 7

A method of identifying, from image data acquired in a nuclear medicine study of a patient's body, an anatomical feature of interest, comprising: conducting a nuclear medicine study and thereby acquiring an image of the feature, said image including, for each image pixel, an intensity representing a number of detected scintillation events which corresponds to the location of that pixel in the patient's body; mapping the image to a local curvature image wherein only pixels with local intensity maxima and minima have non-zero values; grouping together, in accordance with their connectedness, at least some of such non-zero value pixels, to form maxima line segments composed exclusively of pixels with local intensity maxima and minima line segments composed exclusively of pixels with local intensity minima; and determining which of said line segments correspond with the feature by identifying whether said line segments satisfy constraints which have been empirically determined to relate to the feature.

Claim 8

A method of identifying, from image data acquired in a nuclear medicine study of a patient's body, an anatomical feature of interest, comprising: conducting a nuclear medicine study and thereby acquiring an image of the feature, said image including, for each image pixel, an intensity representing a number of detected scintillation events which corresponds to the location of that pixel in the patient's body; mapping the image to a local curvature image wherein only pixels with local intensity maxima and minima have non-zero values; grouping together, in accordance with their connectedness, at least some of such non-zero value pixels, to form maxima line segments composed exclusively of pixels with local intensity maxima and minima line segments composed exclusively of pixels with local intensity minima; and determining which of said line segments correspond with the feature by identifying whether said line segments satisfy constraints which have been empirically determined to relate to the feature.

Claim 9

A method of optimizing the position of a scintillation camera detector with respect to a target organ within the body of a patient and thereby optimizing image data acquired in a nuclear medicine study, comprising: acquiring a first image of the target organ at an initially preferred position of the detector with respect to the patient's body, said first image including, for each image pixel, an intensity representing a number of detected scintillation events which corresponds to the location of that pixel in the patient's body; establishing, on the basis of the target organ, a scan curve and a scan direction; scanning the first image with the scan curve along the scan direction and registering, for each location of the scan curve, the pixels with local intensity maxima and minima; grouping together, in accordance with their connectedness, some of such registered pixels, to form maxima line segments composed exclusively of pixels with local intensity maxima and minima line segments composed exclusively of pixels with local intensity minima; determining which of said line segments correspond with anatomical features of the target organ by identifying whether said line segments satisfy constraints which have been empirically determined to relate to said features; ascertaining, from the line segments which have been so determined to correspond to the feature, a current position of the scintillation camera detector with respect to said target organ; establishing a second preferred position of the scintillation camera detector with respect to the target organ; acquiring a second image of the target organ at said second preferred position of the detector with respect to the patient's body, said second image including second image pixels and for each second image pixel, an intensity representing that number of detected scintillation events which correspond to the location of that pixel in the patient's body; scanning the second image with the scan curve along the scan direction and registering, for each location of the scan curve, the second image pixels with local intensity maxima and minima; grouping together, in accordance with their connectedness, some of such registered second image pixels, to form second image maxima line segments composed exclusively of second image pixels with local intensity maxima and second image minima line segments composed exclusively of second image pixels with local intensity minima; determining which of said second image line segments correspond with anatomical features of the target organ by identifying whether said second image line segments satisfy constraints which have been empirically determined to relate to said features; and ascertaining, from the second image line segments which have been so determined to correspond to the feature, a current position of the scintillation camera detector with respect to said target organ.

Claim 10

A method of optimizing the position of a scintillation camera detector with respect to a target organ within the body of a patient and thereby optimizing image data acquired in a nuclear medicine study, comprising: acquiring a first image of the target organ at an initially preferred position of the detector with respect to the patient's body, said first image including, for each image pixel, an intensity representing a number of detected scintillation events which corresponds to the location of that pixel in the patient's body; establishing, on the basis of the target organ, a scan curve and a scan direction; scanning the first image with the scan curve along the scan direction and registering, for each location of the scan curve, the pixels with local intensity maxima and minima; grouping together, in accordance with their connectedness, some of such registered pixels, to form maxima line segments composed exclusively of pixels with local intensity maxima and minima line segments composed exclusively of pixels with local intensity minima; determining which of said line segments correspond with anatomical features of the target organ by identifying whether said line segments satisfy constraints which have been empirically determined to relate to said features; ascertaining, from the line segments which have been so determined to correspond to the feature, a current position of the scintillation camera detector with respect to said target organ; establishing a second preferred position of the scintillation camera detector with respect to the target organ; acquiring a second image of the target organ at said second preferred position of the detector with respect to the patient's body, said second image including second image pixels and for each second image pixel, an intensity representing that number of detected scintillation events which correspond to the location of that pixel in the patient's body; scanning the second image with the scan curve along the scan direction and registering, for each location of the scan curve, the second image pixels with local intensity maxima and minima; grouping together, in accordance with their connectedness, some of such registered second image pixels, to form second image maxima line segments composed exclusively of second image pixels with local intensity maxima and second image minima line segments composed exclusively of second image pixels with local intensity minima; determining which of said second image line segments correspond with anatomical features of the target organ by identifying whether said second image line segments satisfy constraints which have been empirically determined to relate to said features; and ascertaining, from the second image line segments which have been so determined to correspond to the feature, a current position of the scintillation camera detector with respect to said target organ.

Claim 13

A method of identifying a patient's cardiac ventricles and interventricular septum from image data acquired in a gated cardiac bloodpool study of the patient's heart, comprising: acquiring a nuclear medicine image of the heart wherein the interventricular septum extends generally vertically from the top of the image to the bottom of the image, said image including, for each image pixel, an intensity representing a number of detected scintillation events which corresponds to the location of that pixel in the patient's heart; scanning the image with a horizontally extending line which is moved in a direction that is generally parallel to the patient's interventricular septum and registering, for each vertical location of the horizontally extending scan line, the pixels with local intensity maxima and minima; grouping together, in accordance with their connectedness, some of such registered pixels, to form maxima line segments composed exclusively of pixels with local intensity maxima and minima line segments composed exclusively of pixels with local intensity minima; identifying S-patterns wherein a minima line segment intervenes, along the horizontally extending scan line, between two maxima line segments; and extracting, from all such identified S-patterns, and in accordance with constraints which have been empirically determined to relate to the interventricular septum and the cardiac ventricles, that single S-pattern which best corresponds to the long axes of the ventricles and the intervening interventricular septum.

Claim 14

A method of identifying a patient's cardiac ventricles and interventricular septum from image data acquired in a gated cardiac bloodpool study of the patient's heart, comprising: acquiring a nuclear medicine image of the heart wherein the interventricular septum extends generally vertically from the top of the image to the bottom of the image, said image including, for each image pixel, an intensity representing a number of detected scintillation events which corresponds to the location of that pixel in the patient's heart; scanning the image with a horizontally extending line which is moved in a direction that is generally parallel to the patient's interventricular septum and registering, for each vertical location of the horizontally extending scan line, the pixels with local intensity maxima and minima; grouping together, in accordance with their connectedness, some of such registered pixels, to form maxima line segments composed exclusively of pixels with local intensity maxima and minima line segments composed exclusively of pixels with local intensity minima; identifying S-patterns wherein a minima line segment intervenes, along the horizontally extending scan line, between two maxima line segments; and extracting, from all such identified S-patterns, and in accordance with constraints which have been empirically determined to relate to the interventricular septum and the cardiac ventricles, that single S-pattern which best corresponds to the long axes of the ventricles and the intervening interventricular septum.