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:
Jun. 02, 2020

Filed:

Nov. 16, 2018
Applicant:

Siemens Healthcare Diagnostics Inc., Tarrytown, NY (US);

Inventors:

Noha El-Zehiry, Plainsboro, NJ (US);

Shanhui Sun, Princeton, NJ (US);

Bogdan Georgescu, Plainsboro, NJ (US);

Lance Ladic, Robbinsville, NJ (US);

Ali Kamen, Skillman, NJ (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G03H 1/04 (2006.01); G06K 9/62 (2006.01); G01N 15/14 (2006.01); G06T 7/136 (2017.01); G01N 33/49 (2006.01); G06K 9/46 (2006.01); G06T 7/00 (2017.01); G01N 15/00 (2006.01); G01N 15/10 (2006.01); G03H 1/00 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00147 (2013.01); G01N 15/1463 (2013.01); G01N 33/49 (2013.01); G03H 1/0443 (2013.01); G06K 9/00127 (2013.01); G06K 9/4604 (2013.01); G06K 9/6268 (2013.01); G06K 9/6269 (2013.01); G06T 7/0012 (2013.01); G06T 7/136 (2017.01); G01N 2015/008 (2013.01); G01N 2015/1006 (2013.01); G03H 2001/005 (2013.01); G06T 2207/30104 (2013.01);
Abstract

A method for analyzing digital holographic microscopy (DHM) data for hematology applications includes receiving a plurality of DHM images acquired using a digital holographic microscopy system. One or more connected components are identified in each of the plurality of DHM images and one or more training white blood cell images are generated from the one or more connected components. A classifier is trained to identify a plurality of white blood cell types using the one or more training white blood cell images. The classifier may be applied to a new white blood cell image to determine a plurality of probability values, each respective probability value corresponding to one of the plurality of white blood cell types. The new white blood cell image and the plurality of probability values may then be presented in a graphical user interface.


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