Method and apparatus for removing tissue autofluorescence
AssigneeGeneral Electric Company
InventorsAli Can, Michael John Gerdes, Musodiq Olatayo Bello, Xiaodong Tao, Francis Edward Pavan-Woolfe, Roshni Bhagalia
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Abstract
Techniques for removing image autoflourescence from fluorescently stained biological images are provided herein. The techniques utilize non-negative matrix factorization that may constrain mixing coefficients to be non-negative. The probability of convergence to local minima is reduced by using smoothness constraints. The non-negative matrix factorization algorithm provides the advantage of removing both dark current and autofluorescence.
Claims21
A method for reducing autofluorescence in an image of a biological material, comprising the steps of:
- accessing image data from two or more images of the biological material, wherein at least one of the images is fluorescently stained for a marker of interest and wherein at least one of the images is a reference image;
- analyzing the image data of the two or more images using a non-negative matrix factorization algorithm to generate an estimate of the autofluorescence in at least one of the two or more images;
- and
- generating an output of a corrected image with reduced autofluorescence.
A non-transitory computer-readable medium comprising instructions for:
- accessing image data from two or more images of the biological material, wherein at least one of the images is fluorescently stained for a marker of interest and wherein at least one of the images is a reference image;
- analyzing the image data of the two or more images using a non-negative matrix factorization algorithm to generate an estimate of the autofluorescence in at least one of the two or more images;
- and
- generating an output of a corrected image with reduced autofluorescence.
An image analysis system comprising:
- a processor adapted to receive image data from two or more images of the biological material, wherein at least one of the images is fluorescently stained for a marker of interest and wherein at least one of the images is a reference image the processor adapted to run instructions for:
- analyzing the image data of the two or more images using a non-negative matrix factorization algorithm to generate an estimate of the autofluorescence in at least one of the two or more images;
- and
- generating an output of a corrected image with reduced autofluorescence.
Dependencies are inferred from the claim text.