Generating image-based diagnostic tests by optimizing image analysis and data mining of co-registered images
First Claim
1. A method comprising:
- (a) dividing each digital image of a plurality of slices of tissue of a patient into tiles, wherein the tiles obtained from digital images of different slices of tissue are coregistered with each other to form a stack of tiles;
(b) generating first objects that are linked to pixels of the tiles, wherein a first rule set defines which pixels are linked to each of the first objects;
(c) using a second rule set to generate first numerical data by measuring a first characteristic of the first objects located in each of the tiles;
(d) generating a heat map by aggregating the first numerical data associated with each stack of tiles, wherein each stack of tiles is used to generate a pixel of the heat map;
(e) generating second objects from the heat map, wherein a third rule set defines which pixels of the heat map are linked to each of the second objects;
(f) using a fourth rule set to generate second numerical data by measuring a second characteristic of the second objects detected in the heat map;
(g) determining how well the second numerical data correlates with clinical data for the patient;
(h) improving how well the second numerical data correlates with the clinical data for the patient by modifying the first rule set, the second rule set, the third rule set and the fourth rule set and then repeating (b) through (g); and
(i) defining an image-based diagnostic test based on the first rule set, the second rule set, the third rule set and the fourth rule set.
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Abstract
A method for generating an image-based test improves diagnostic accuracy by iteratively modifying rule sets governing image and data analysis of coregistered image tiles. Digital images of stained tissue slices are divided into tiles, and tiles from different images are coregistered. First image objects are linked to selected pixels of the tiles. First numerical data is generated by measuring the first objects. Each pixel of a heat map aggregates first numerical data from coregistered tiles. Second objects are linked to selected pixels of the heat map. Measuring the second objects generates second numerical data. The method improves how well second numerical data correlates with clinical data of the patient whose tissue is analyzed by modifying the rule sets used to generate the first and second objects and the first and second numerical data. The test is defined by those rule sets that produce the best correlation with the clinical data.
16 Citations
25 Claims
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1. A method comprising:
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(a) dividing each digital image of a plurality of slices of tissue of a patient into tiles, wherein the tiles obtained from digital images of different slices of tissue are coregistered with each other to form a stack of tiles; (b) generating first objects that are linked to pixels of the tiles, wherein a first rule set defines which pixels are linked to each of the first objects; (c) using a second rule set to generate first numerical data by measuring a first characteristic of the first objects located in each of the tiles; (d) generating a heat map by aggregating the first numerical data associated with each stack of tiles, wherein each stack of tiles is used to generate a pixel of the heat map; (e) generating second objects from the heat map, wherein a third rule set defines which pixels of the heat map are linked to each of the second objects; (f) using a fourth rule set to generate second numerical data by measuring a second characteristic of the second objects detected in the heat map; (g) determining how well the second numerical data correlates with clinical data for the patient; (h) improving how well the second numerical data correlates with the clinical data for the patient by modifying the first rule set, the second rule set, the third rule set and the fourth rule set and then repeating (b) through (g); and (i) defining an image-based diagnostic test based on the first rule set, the second rule set, the third rule set and the fourth rule set. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A method comprising:
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(a) dividing a first digital image and a second digital image into tiles, wherein the first digital image is of a first slice of tissue of a patient that is stained with a first biomarker, wherein the second digital image is of a second slice of tissue of the patient that is stained with a second biomarker, and wherein the tiles of the first digital image are coregistered with the tiles of the second digital image; (b) generating first objects that are linked to pixels of the tiles, wherein a first rule set defines which pixels are linked to each of the first objects; (c) generating first numerical data by measuring the first objects using a second rule set; (d) generating a heat map by aggregating the first numerical data associated with coregistered tiles, wherein each pixel of the heat map is generated from coregistered tiles; (e) generating second objects from the heat map, wherein a third rule set defines which pixels of the heat map are linked to each of the second objects; (f) generating second numerical data by measuring the second objects using a fourth rule set; (g) improving how well the second numerical data correlates with clinical data for the patient by modifying the fourth rule set and then repeating the generating of the second numerical data in (f); and (h) defining an image-based diagnostic test based on the first rule set, the second rule set, the third rule set and the fourth rule set. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17)
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18. A method comprising:
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(a) dividing a first digital image and a second digital image into tiles, wherein the first digital image is of a first slice of tissue of a patient that is stained with a first biomarker, wherein the second digital image is of a second slice of tissue of the patient that is stained with a second biomarker, and wherein a first tile of the first digital image is coregistered with a second tile of the second digital image; (b) generating a data network that includes first tile objects that are linked to selected pixels of the first tile and second tile objects that are linked to pixels of the second tile; (c) generating a heat map, wherein each pixel of the heatmap has a color dependent on information obtained by analyzing both the first tile objects and the second tile objects; (d) generating heat map objects that are linked to selected pixels of the heatmap; (e) using a rule set to generate numerical data by measuring the heat map objects; (f) improving how well the numerical data correlates with an actual clinical outcome of the patient by modifying the rule set and repeating (e); and (g) defining an image-based test that generates a predicted clinical outcome using the rule set. - View Dependent Claims (19, 20, 21, 22, 23, 24, 25)
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Specification