Method for determining the contour of an in vivo organ using multiple image frames of the organ
First Claim
1. A method for automatically determining a contour of an internal organ in a patient based upon digital image data of a region in which the organ is disposed, said image data representing a sequence of image frames of the region made over an interval of time during which a wall of the organ has completed at least one cycle of movement, the wall of the organ undergoing repetitive cycles of movement as part of the organ'"'"'s physiological function, each image frame of said sequence of image frames comprising a plurality of pixels, said method comprising the steps of:
- (a) developing an initial estimate of a region bounded by the contour of the organ in each image frame of the sequence, by comparing the image data with parameters derived from training data that were previously produced through manual evaluation of a plurality of image frames over a corresponding cycle for each of a plurality of corresponding organs in other individuals, said parameters that are derived from the training data being used to assign classes to the pixels comprising each of the image frames of the sequence, said classes indicating pixels that are most likely inside the contour of the organ in each image frame; and
(b) determining a border of the organ in a portion of the contour adjacent to a tissue mass lying outside the organ, by masking out the tissue mass, thereby refining the initial estimate of the region bounded by the contour of the organ so that the border of the organ is more accurately defined in said portion of the contour.
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Accused Products
Abstract
An automated method for evaluating image data taken over a sequence of image frames to determine a contour of a left ventricle (LV). The sequence of image frames are converted to digital data that identify a gray scale value for each pixel in each image frame. An initial LV region is estimated based upon training data parameters derived from processing manually drawn contours of the LV in the hearts of other individuals, corresponding to the sequence of image frames being analyzed. Prior to producing the initial estimate, the location of the aortic valve in the sequence of image frames for the patient is determined to serve as a reference. The data derived frown the contours of the LVs for the other hearts are rotated and translated relative to this reference to insure that the training data information corresponds to the position and orientation of the LV being analyzed. In addition, the effects of tissue mass comprising a diaphragm adjacent to the inferior portion of the LV are compensated by masking out the diaphragm. Uncertainty of the contour of the LV in this portion due to the presence of the diaphragm is thereby minimized. The resulting automatically determined contours of each image frame can be displayed to enable a physician to more readily diagnose physiological defects of the heart.
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Citations
26 Claims
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1. A method for automatically determining a contour of an internal organ in a patient based upon digital image data of a region in which the organ is disposed, said image data representing a sequence of image frames of the region made over an interval of time during which a wall of the organ has completed at least one cycle of movement, the wall of the organ undergoing repetitive cycles of movement as part of the organ'"'"'s physiological function, each image frame of said sequence of image frames comprising a plurality of pixels, said method comprising the steps of:
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(a) developing an initial estimate of a region bounded by the contour of the organ in each image frame of the sequence, by comparing the image data with parameters derived from training data that were previously produced through manual evaluation of a plurality of image frames over a corresponding cycle for each of a plurality of corresponding organs in other individuals, said parameters that are derived from the training data being used to assign classes to the pixels comprising each of the image frames of the sequence, said classes indicating pixels that are most likely inside the contour of the organ in each image frame; and (b) determining a border of the organ in a portion of the contour adjacent to a tissue mass lying outside the organ, by masking out the tissue mass, thereby refining the initial estimate of the region bounded by the contour of the organ so that the border of the organ is more accurately defined in said portion of the contour. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15. A method for automatically determining a contour of an internal organ in a patient based upon digital image data of a region in which the organ is disposed, said image data representing a sequence of image frames of the region made over an interval of time during which a wall of the organ has completed at least one cycle of movement, the wall of the organ undergoing repetitive cycles of movement as part of the organ'"'"'s physiological function, each image frame of said sequence of image frames comprising a plurality of pixels, said method comprising the step of:
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(a) aligning a reference location associated with an anatomical feature of the organs represented by training data with a reference location associated with a corresponding anatomical feature of the organ in the patient, where the training data were previously produced from a plurality of image frames over a corresponding cycle for each of a plurality of corresponding organs in other individuals; and (b) developing an estimate of a region bounded by the contour of the organ in each image frame of the sequence, based upon a comparison of the image data with parameters derived through manual evaluation of the training data, said parameters derived from the training data being used to assign classes to the pixels comprising each of the image frames of the sequence, said classes indicating pixels that are most likely inside the contour of the organ in each image frame. - View Dependent Claims (16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26)
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Specification