Applying pixelwise descriptors to a target image that are generated by segmenting objects in other images
First Claim
1. A method comprising:
- dividing images of tissue of cancer patients into tiles;
separating the tiles into clusters, wherein each of the clusters has tiles with similar colors;
identifying a matching cluster whose tiles have colors that most closely match the colors of a target image of tissue of a target patient;
segmenting the tiles of the matching cluster into objects;
classifying the objects into classes;
assigning a color to each object class;
generating pixelwise descriptors that associate an object class with each pixel of the tiles of the matching cluster based on colors of other pixels at predetermined offsets from the classified pixel; and
generating a pixel heat map by applying the pixelwise descriptors to each pixel of the target image without segmenting the target image into objects, wherein each pixel of the target image has the color assigned to the object class associated with that pixel.
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Accused Products
Abstract
Both pixel-oriented analysis and the more accurate yet slower object-oriented analysis are used to recognize patterns in images of stained cancer tissue. Images of tissue from other patients that are similar to tissue of a target patient are identified using the standard deviation of color in the images. Object-oriented segmentation is then used to segment small portions of the images of the other patients into object exhibiting object characteristics. Pixelwise descriptors associate each pixel in the remainder of the images with object characteristics based on the color of pixels at predetermined offsets from the characterized pixel. Pixels in the image of the target patient are assigned object characteristics without performing the slow segmentation of the image into objects. A pixel heat map is generated from the target image by assigning pixels the color corresponding to the object characteristic that the pixelwise descriptors indicate is most likely associated with each pixel.
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Citations
20 Claims
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1. A method comprising:
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dividing images of tissue of cancer patients into tiles; separating the tiles into clusters, wherein each of the clusters has tiles with similar colors; identifying a matching cluster whose tiles have colors that most closely match the colors of a target image of tissue of a target patient; segmenting the tiles of the matching cluster into objects; classifying the objects into classes; assigning a color to each object class; generating pixelwise descriptors that associate an object class with each pixel of the tiles of the matching cluster based on colors of other pixels at predetermined offsets from the classified pixel; and generating a pixel heat map by applying the pixelwise descriptors to each pixel of the target image without segmenting the target image into objects, wherein each pixel of the target image has the color assigned to the object class associated with that pixel. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A method comprising:
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dividing digital images of stained tissue of cancer patients into tiles; identifying clusters of tiles whose pixel characteristics are similar; identifying a matching cluster of tiles whose pixel characteristics most closely match the pixel characteristics of a target digital image of stained tissue of a target patient, wherein the pixel characteristics used to identify the matching cluster of tiles are determined only from regions on the tiles that exhibit an intermediate degree of local contrast; segmenting the tiles of the matching cluster into objects; determining an object class to which each of the objects belongs; generating pixelwise descriptors that describe the object class to which a characterized pixel most probably belongs based on a quality of a second pixel at a predetermined offset from the characterized pixel; and generating a pixel heat map by applying the pixelwise descriptors to each pixel of the target digital image without segmenting the target digital image into objects, wherein each pixel of the target digital image has a color assigned to the object class to which that pixel most probably belongs. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A method of identifying cancer tissue comprising:
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dividing images of tissue of a plurality of cancer patients into tiles; separating the tiles into clusters having similar colors by successively separating the tiles into clusters until each cluster exhibits a standard deviation of color whose magnitude falls below a predetermined threshold; identifying a matching cluster of tiles whose colors most closely match the colors of a target image of tissue of a target cancer patient; segmenting the tiles of the matching cluster into objects; classifying the objects into classes; assigning a color to each object class; generating pixelwise descriptors that associate each pixel of the tiles of the matching cluster to an object class based on colors of other pixels at predetermined offsets from the classified pixel; and generating a pixel heat map by applying the pixelwise descriptors to each pixel of the target image without segmenting the target image into objects. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20)
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Specification