Microcalcification detection and classification in radiographic images
First Claim
1. A method for detecting an anomaly in an image, the method comprising:
- convolving, by a processor, a digital image with a smoothing filter to create a plurality of first convolved images at differing scales;
convolving, by the processor, each of the plurality of first convolved images with a second derivative filter, thereby creating a plurality of second convolved images, each of the plurality of first convolved images and a corresponding one of the plurality of second convolved images corresponding to respective ones of a plurality of stages;
creating, by the processor, a plurality of surgery masks, each surgery mask based at least in part on one of the plurality of the second convolved images of a current stage and one of the plurality of second convolved images from a previous stage;
determining, by the processor, a neighborhood median for each pixel location of the plurality of surgery masks;
identifying, by the processor, one or more peaks in the digital image based at least in part upon the second convolved image from the current stage, the first convolved image from the previous stage, and the neighborhood medians for the current stage; and
storing, by the processor in a non-transitory computer-readable memory, a peak list comprising selected one or more of the one or more peaks having a corresponding contrast ratio higher than a contrast ratio threshold.
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Accused Products
Abstract
An analysis of a digitized image is provided. The digitized image is repeatedly convolved to form first convolved images, which first convolved images are convolved a second time to form second convolved images. Each first convolved image and the respective second convolved image representing a stage, and each stage represents a different scale or size of anomaly. As an example, the first convolution may utilize a Gaussian convolver, and the second convolution may utilize a Laplacian convolver, but other convolvers may be used. The second convolved image from a current stage and the first convolved image from a previous stage are used with a neighborhood median determined from the second convolved image from the current stage by a peak detector to detect peaks, or possible anomalies for that particular scale.
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Citations
20 Claims
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1. A method for detecting an anomaly in an image, the method comprising:
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convolving, by a processor, a digital image with a smoothing filter to create a plurality of first convolved images at differing scales; convolving, by the processor, each of the plurality of first convolved images with a second derivative filter, thereby creating a plurality of second convolved images, each of the plurality of first convolved images and a corresponding one of the plurality of second convolved images corresponding to respective ones of a plurality of stages; creating, by the processor, a plurality of surgery masks, each surgery mask based at least in part on one of the plurality of the second convolved images of a current stage and one of the plurality of second convolved images from a previous stage; determining, by the processor, a neighborhood median for each pixel location of the plurality of surgery masks; identifying, by the processor, one or more peaks in the digital image based at least in part upon the second convolved image from the current stage, the first convolved image from the previous stage, and the neighborhood medians for the current stage; and storing, by the processor in a non-transitory computer-readable memory, a peak list comprising selected one or more of the one or more peaks having a corresponding contrast ratio higher than a contrast ratio threshold. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A system for identifying anomalies in a digitized image, the system comprising:
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a processor; and a non-transitory computer readable storage medium storing programming for execution by the processor, the programming including instructions for; convolving a digitized image with a smoothing filter, creating a first convolved image; convolving the first convolved image with a second derivative filter, creating a second convolved image; determining a neighborhood median for each pixel in the second convolved image; identifying pixels in the digitized image having peak values, in accordance with the digitized image, the second convolved image, and the neighborhood median for each pixel in the second convolved image; and storing a peak list comprising selected one or more of the identified pixels having a corresponding contrast ratio higher than a contrast ratio threshold. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A computer program product for identifying anomalies, the computer program product having a non-transitory computer-readable medium with a computer program embodied thereon, the computer program comprising:
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computer program code for convolving a digitized image with a smoothing filter, thereby creating a plurality of first convolved images, each of the convolved images corresponding to a different scale; computer program code for convolving each of the plurality of first convolved images with a second derivative filter, creating a plurality of second convolved images; computer program code for determining a neighborhood median for each pixel of each of the plurality of second convolved images; computer program code for identifying peak regions based at least in part upon one of the plurality of first convolved images and one of the second convolved images, the one of the second convolved images corresponding to the one of the plurality of first convolved images after being convolved by the convolving a digitized image and the convolving each of the plurality of first convolved images; and computer program code for storing a peak list comprising selected one or more of the peak regions having a corresponding contrast ratio higher than a contrast ratio threshold. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification