US 2017/0323445 A1 · MORPHOLOGY IDENTIFICATION IN TISSUE SAMPLES BASED ON COMPARISON TO NAMED FEATURE VECTORS

Abstract

Locating morphology in a tissue sample is achieved with devices and methods involving storage of a plurality of feature vectors, each associated with a specific named superpixel of a larger image of a tissue sample from a mammalian body. A microscope outputs, in some embodiments, a live image of an additional tissue sample or a digitized version of the output is used. At least one superpixel of the image is converted into a feature vector and a nearest match between the first feature vector and the plurality of stored feature vectors is made. A first name suggestion is then made based on the nearest match comparison to a store feature vector. Further, regions of interest within the image can be brought to a viewer's attention based on their past history of selection, or that of others.

Claims22

Dependent claims

A method of locating morphology in a tissue sample, comprises the steps of:

obtaining a first and second tissue sample, each removed from a mammalian body;
digitizing an image of said first tissue sample and said second tissue sample;
receiving a selection of at least one superpixel of said image of said first tissue sample;
receiving a named morphology for said at least one superpixel and converting said at least one superpixel into a first feature vector;
extracting superpixels of said image of said second tissue sample and converting each superpixel of said second image of said second tissue into second feature vectors;
finding, within said second feature vectors of said second tissue, a nearest match feature vector to said first feature vector;
and
indicating that a superpixel of said second image associated with said nearest match feature vector is possibly a representation of said named morphology.

5 more elements

Dependencies are inferred from the claim text.

Morphology identification in tissue samples based on comparison to named feature vectors

Life of this patent

Morphology identification in tissue samples based on comparison to named feature vectors

Life of this patent

Abstract

Claims22