System and method for rapidly identifying pathogens, bacteria and abnormal cells
First Claim
1. A method for processing an image of a specimen or dental x-ray to identify a pathogen within the specimen or dental x-ray, comprising the steps of:
- providing an image of a specimen or dental x-ray;
providing a parallel processing computing platform;
implementing a recursive hierarchical segmentation algorithm on the parallel processing computing platform and processing the image with the recursive hierarchical segmentation algorithm to isolate at least one segment of the provided image that has a feature that is of interest;
processing the isolated segment with a data mining algorithm to extract particular image data from the isolated segment; and
processing the extracted particular image data and at least one reference image with an optical recognition algorithm to determine if the extracted image data matches the at least one reference image.
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Abstract
The present invention achieves rapid identification of pathogens, bacteria, cancer cells and other abnormal human and animal cells. In one embodiment, the system of the present invention comprises a first subsystem that obtains and processes images of specimens of pathogens, bacteria, and other abnormal cells, and a second subsystem that accepts the images, isolates the particular features of the image using advanced image segmentation, and then rapidly and accurately identifies the pathogens, bacteria and other abnormal cells by using a pattern recognition process wherein the segmented or isolated features of the original image are compared to known reference images.
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Citations
12 Claims
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1. A method for processing an image of a specimen or dental x-ray to identify a pathogen within the specimen or dental x-ray, comprising the steps of:
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providing an image of a specimen or dental x-ray; providing a parallel processing computing platform; implementing a recursive hierarchical segmentation algorithm on the parallel processing computing platform and processing the image with the recursive hierarchical segmentation algorithm to isolate at least one segment of the provided image that has a feature that is of interest; processing the isolated segment with a data mining algorithm to extract particular image data from the isolated segment; and processing the extracted particular image data and at least one reference image with an optical recognition algorithm to determine if the extracted image data matches the at least one reference image. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A system for processing an image of a specimen or dental x-ray to identify a pathogen within the specimen or dental x-ray, comprising:
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a device to provide an image of a specimen or dental x-ray; a digitizer to digitize the provided image; a first data storage device to store the digitized images; a second data storage device having at least one reference image stored therein; a parallel processing computing platform configured to implement a recursive hierarchical segmentation algorithm, a data mining algorithm and an optical recognition algorithm; a work station computer in data communication with the parallel processing computing platform, the work station computer comprising electronic data communication hardware and software that enables the work station computer to control the parallel processing computing platform to (i) process the digitized image with the recursive hierarchical segmentation algorithm to isolate at least one segment of the digitized image that has a feature that is of interest (ii) process the isolated segment with the data mining algorithm to extract particular image data from the isolated segment, and (iii) process the extracted particular image data and each of the reference images with the optical recognition algorithm to determine if the extracted image data matches any of the reference images; and a display device in data communication with the work station computer to display the extracted image data and the results of processing the extracted image data and the reference image with the optical recognition algorithm. - View Dependent Claims (10, 11, 12)
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Specification