Classifying image features
First Claim
Patent Images
1. A method assessing a tissue sample, the method comprising using one or more processors to perform the following steps:
- decomposing a set of spectral images of the tissue sample into a set of unmixed images, wherein each member of the unmixed image set corresponds to a spectral contribution from a different component in the tissue sample; and
using a machine-learning classifier to classify different regions of the tissue sample into respective classes based on an image stack comprising one or more of the unmixed images.
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Abstract
Methods are disclosed for classifying different parts of a sample into respective classes based on an image stack that includes one or more images.
119 Citations
36 Claims
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1. A method assessing a tissue sample, the method comprising using one or more processors to perform the following steps:
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decomposing a set of spectral images of the tissue sample into a set of unmixed images, wherein each member of the unmixed image set corresponds to a spectral contribution from a different component in the tissue sample; and using a machine-learning classifier to classify different regions of the tissue sample into respective classes based on an image stack comprising one or more of the unmixed images. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A system for assessing a tissue sample or a blood sample, the system, comprising:
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a light source; light conditioning optics positioned to direct light from the source to the sample; a detector configured to detect light from the sample and record a set of spectral images; light collecting optics positioned to direct the light from the sample to the detector; and one or more electronic processors configured to; decompose the set of spectral images into a set of unmixed images, wherein each member of the unmixed image set corresponds to a spectral contribution from a different component in the sample; and use a machine-learning classifier to classify different regions of the sample into respective classes based on an image stack comprising one or more of the unmixed images. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
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26. A method for analyzing a blood sample, the method comprising using one or more processors to perform the following steps:
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decomposing a set of spectral images of the blood sample into a set of unmixed images, wherein each member of the unmixed image set corresponds to a spectral contribution from a different component in the blood sample; and using a machine-learning classifier to classify different cells of the blood sample into respective classes based on an image stack comprising one or more of the unmixed images. - View Dependent Claims (27, 28, 29, 30, 31, 32, 33, 34, 35, 36)
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Specification