The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 13, 2018

Filed:

Dec. 21, 2016
Applicant:

Ventana Medical Systems, Inc., Tucson, AZ (US);

Inventors:

Christophe Chefd'hotel, Sunnyvale, CA (US);

Srinivas Chukka, San Jose, CA (US);

Xiuzhong Wang, San Jose, CA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/12 (2017.01); G06T 7/194 (2017.01); G06T 7/136 (2017.01); G06T 7/00 (2017.01); G06T 7/13 (2017.01); G06K 9/46 (2006.01);
U.S. Cl.
CPC ...
G06T 7/12 (2017.01); G06T 7/0012 (2013.01); G06T 7/13 (2017.01); G06T 7/136 (2017.01); G06T 7/194 (2017.01); G06K 9/4604 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/10056 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20164 (2013.01); G06T 2207/30024 (2013.01);
Abstract

Systems and methods for generating a locally adaptive threshold image for foreground detection performing operations including creating a saliency edge strength image or layer indicating edge or border pixels of the nuclei by performing tensor voting on pixels neighboring the initial edge pixels within an image region to refine true edges are featured. Further, for each of a plurality of regions or blocks of the image, an adaptive threshold image is determined by sampling a foreground pixel and a background pixel for each initial edge pixel or refined edge pixel, generating histograms for both background and foreground saliency (or gradient magnitude) modulated histograms, determining a threshold range for each block of the image, and interpolating the threshold at each pixel based on the threshold range at each block. Comparing the input image with the resulting locally adaptive threshold image enables extraction of significantly improved foreground.


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