System and method for detecting anomalous targets including cancerous cells
First Claim
1. A system for identifying anomalous targets comprising:
- one or more imaging subsystems to generate track files from an image comprising targets;
an image processing subsystem to extract features from the track files; and
a discrimination subsystem to generate a probabilistic belief function from the extracted features for generating an output indicating that at least some of the targets are anomalous.
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Abstract
A method and system for identifying anomalous cells includes an imaging subsystem to generate a track file from collected images of cells, a image processing subsystem to extract features from the track file and generate feature sets for particular cells, and a discrimination subsystem to generate a probabilistic belief function from the feature sets to determine a probability that at least some of the cells are anomalous. The images may include sample cells from a tissue sample. In embodiments, the imaging subsystem may collect images from photographs and may also collect images from a microscope. In embodiments, the discrimination subsystem may perform both supervised and unsupervised training to update the belief functions learning from known anomalous cells and cells with know anomalous features to enhance its accuracy over time.
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Citations
32 Claims
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1. A system for identifying anomalous targets comprising:
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one or more imaging subsystems to generate track files from an image comprising targets;
an image processing subsystem to extract features from the track files; and
a discrimination subsystem to generate a probabilistic belief function from the extracted features for generating an output indicating that at least some of the targets are anomalous. - 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 cancerous-cell identification system comprising:
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an imaging subsystem to generate track files from one or more images of a tissue sample;
an image processing subsystem to extract features of cells from the track file; and
a discrimination subsystem to generate a probabilistic belief function from the extracted features for generating an output indicating that at least some of the cells within the one or more images are cancerous. - View Dependent Claims (22, 23, 24)
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25. A method for identifying anomalous targets comprising:
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generating track files from an image comprising targets;
extracting features from the track file; and
generating a probabilistic belief function from the extracted features for generating an output indicating that at least some of the targets are anomalous. - View Dependent Claims (26, 27, 28, 29, 30)
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31. An article comprising a storage medium having stored thereon instructions, that when executed by a computing platform, result in:
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generation of track files from an image comprising targets;
extraction of features from the track file; and
generation of a probabilistic belief function from the extracted features for generating an output indicating that at least some of the targets are anomalous. - View Dependent Claims (32)
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Specification