Method and apparatus for detecting a desired behavior in digital image data
First Claim
1. An apparatus for detecting a desired behavior within digital image data of a plurality of pixels, comprising:
- storage means for prestoring a plurality of reference images;
calculating means for calculating a plurality of features for each of a plurality of pixels for each of the reference images;
computing means for creating a binary decision tree from calculated features of random samples of pixels from each of the reference images, said calculating means further calculating a plurality of features for each of the pixels of the digital image data;
input means for inputting each of the plurality of features of each pixel of the digital image data into the binary decision tree;
determining means for determining a probability, corresponding to the likelihood of a presence of the desired behavior, for each of the pixels of the digital image data based upon binary decision tree results to create a probability image;
filtering means for spatial filtering the probability image to enforce local consensus among neighboring pixels within the probability image; and
output means for outputting the spatially filtered image, wherein at least one of the plurality of features for each of the pixels of the digital image data is calculated by a calculating means including,accessing means for accessing, for each of a plurality of pixels of the digital image data, digital image data of each pixel and pixels surrounding each of the plurality of pixels in predetermined window dimensions,orientation means for computing edge orientation values of the accessed digital image data, for each of the plurality of pixels,histogramming means for histogramming, for each of the plurality of pixels, the computed edge orientation values, andcomputing means for computing a standard deviation of each histogram to create a feature for identifying a probable presence of the desired behavior in each of the plurality of pixels in which the standard deviation of the orientation histogram indicates a characteristic degree of orientation heterogeneity.
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Abstract
A method for detecting stellate lesions in digitized mammographic image data includes the steps of prestoring a plurality of reference images, calculating a plurality of features for each of the pixels of the reference images, and creating a binary decision tree from features of randomly sampled pixels from each of the reference images. Once the binary decision tree has been created, a plurality of features, preferably including an ALOE feature (analysis of local oriented edges), are calculated for each of the pixels of the digitized mammographic data. Each of these plurality of features of each pixel are input into the binary decision tree and a probability is determined, for each of the pixels, corresponding to the likelihood of the presence of a stellate lesion, to create a probability image. Finally, the probability image is spatially filtered to enforce local consensus among neighboring pixels and the spatially filtered image is output.
45 Citations
46 Claims
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1. An apparatus for detecting a desired behavior within digital image data of a plurality of pixels, comprising:
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storage means for prestoring a plurality of reference images; calculating means for calculating a plurality of features for each of a plurality of pixels for each of the reference images; computing means for creating a binary decision tree from calculated features of random samples of pixels from each of the reference images, said calculating means further calculating a plurality of features for each of the pixels of the digital image data; input means for inputting each of the plurality of features of each pixel of the digital image data into the binary decision tree; determining means for determining a probability, corresponding to the likelihood of a presence of the desired behavior, for each of the pixels of the digital image data based upon binary decision tree results to create a probability image; filtering means for spatial filtering the probability image to enforce local consensus among neighboring pixels within the probability image; and output means for outputting the spatially filtered image, wherein at least one of the plurality of features for each of the pixels of the digital image data is calculated by a calculating means including, accessing means for accessing, for each of a plurality of pixels of the digital image data, digital image data of each pixel and pixels surrounding each of the plurality of pixels in predetermined window dimensions, orientation means for computing edge orientation values of the accessed digital image data, for each of the plurality of pixels, histogramming means for histogramming, for each of the plurality of pixels, the computed edge orientation values, and computing means for computing a standard deviation of each histogram to create a feature for identifying a probable presence of the desired behavior in each of the plurality of pixels in which the standard deviation of the orientation histogram indicates a characteristic degree of orientation heterogeneity. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A method for detecting a desired behavior within digital image data of a plurality of pixels, the method comprising the steps of:
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(a) prestoring a plurality of reference images; (b) calculating a plurality of features for each of a plurality of pixels for each of the reference images; (c) creating a binary decision tree from calculated features of random samples of pixels from each of the reference images; (d) calculating a plurality of features for each of the pixels of the digital image data; (e) inputting each of the plurality of features of each pixel of digital image data into the binary decision tree; (f) determining a probability, corresponding to the likelihood of a presence of the desired behavior, for each of the pixels of the digital image data based upon binary decision tree results to create a probability image; (g) spatial filtering the probability image to enforce local consensus among neighboring pixels within the probability image; and (h) outputting the spatially filtered image, wherein at least one of the plurality of features for each of the pixels of the digital image data is calculated, in at least one of steps (b) and (d), by the substeps of, (i) accessing, for each of a plurality of pixels of the digital image data, digital image data of each pixel and pixels surrounding each of the plurality of pixels in predetermined window dimensions, (ii) computing edge orientation values of the accessed digital image data, for each of the plurality of pixels, (iii) histogramming, for each of the plurality of pixels, the computed edge orientation value, and (iv) computing a standard deviation of each histogram to create a feature for identifying a probable presence of the desired behavior in each of the plurality of pixels in which the standard deviation of the orientation histogram indicates a characteristic degree of orientation heterogeneity. - View Dependent Claims (22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40)
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41. An apparatus for detecting a desired behavior within digital image data of a plurality of pixels, comprising:
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storage means for prestoring a plurality of reference images; calculating means for calculating a plurality of features for each of a plurality of pixels for each of the reference images; computing means for creating a binary decision tree from calculated features of random samples of pixels from each of the reference images, said calculating means further calculating a plurality of features for each of the pixels of the digital image data; input means for inputting each of the plurality of features of each pixel of the digital image data into the binary decision tree; determining means for determining a probability, corresponding to the likelihood of a presence of the desired behavior, for each of the pixels of the digital image data based upon binary decision tree results, to create a probability image; filtering means for spatial filtering the probability image to enforce local consensus among neighboring pixels within the probability image; and output means for outputting the spatially filtered image, wherein at least one of the plurality of features for each of the pixels of the digital image data is calculated by a calculating means including, accessing means for accessing, for each of a plurality of pixels of the digital image data, digital image data of each pixel and pixels surrounding each of the plurality of pixels in predetermined window dimensions, orientation means for computing edge orientation values of the accessed digital image data, for each of the plurality of pixels, histogramming means for histogramming, for each of the plurality of pixels, the computed edge orientation values, and detecting means for detecting a probable presence of the desired behavior in each of the plurality of pixels for which the orientation histogram indicates a characteristic degree of orientation heterogeneity. - View Dependent Claims (42, 43)
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44. A method for detecting a desired behavior within digital image data of a plurality of pixels, the method comprising the steps of:
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(a) prestoring a plurality of reference images; (b) calculating a plurality of features for each of a plurality of pixels for each of the reference images; (c) creating a binary decision tree from calculated features of random samples of pixels of each of the reference images; (d) calculating a plurality of features for each of the pixels of the digital image data; (e) inputting each of the plurality of features of each pixel of digital image data into the binary decision tree; (f) determining a probability, corresponding to the likelihood of a presence of the desired behavior, for each of the pixels of the digital image data based upon binary decision tree results to create a probability image; (g) spatial filtering the probability image to enforce local consensus among neighboring pixels within the probability image; and (h) outputting the spatially filtered image, wherein at least one of the plurality of features for each of the pixels of the digital image data is calculated, in at least one of steps (b) and (d), by the substeps of, (i) accessing, for each of a plurality of pixels of the digital image data, digital image data of each pixel and pixels surrounding each of the plurality of pixels in predetermined window dimensions, (ii) computing edge orientation values of the accessed digital image data, for each of the plurality of pixels, (iii) histogramming, for each of the plurality of pixels, the computed edge orientation values; and (iv) detecting a probable presence of the desired behavior in each of the plurality of pixels for which the orientation histogram indicates a characteristic degree of orientation heterogeneity. - View Dependent Claims (45, 46)
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Specification