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:
Apr. 14, 2020

Filed:

Feb. 13, 2018
Applicant:

Tata Consultancy Services Limited, Mumbai, IN;

Inventors:

Monika Sharma, Gurgaon, IN;

Lovekesh Vig, Gurgaon, IN;

Shirish Subhash Karande, Pune, IN;

Anand Sriraman, Pune, IN;

Ramya Sugnana Murthy Hebbalaguppe, Gurgaon, IN;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G16B 10/00 (2019.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); G06K 9/00 (2006.01); G06T 7/00 (2017.01); G16H 30/40 (2018.01); G16B 40/20 (2019.01);
U.S. Cl.
CPC ...
G06K 9/6262 (2013.01); G06K 9/0014 (2013.01); G06K 9/00147 (2013.01); G06K 9/6271 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06T 7/0012 (2013.01); G16B 10/00 (2019.02); G06T 2207/20021 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30024 (2013.01); G16B 40/20 (2019.02); G16H 30/40 (2018.01);
Abstract

The most challenging problems in karyotyping are segmentation and classification of overlapping chromosomes in metaphase spread images. Often chromosomes are bent in different directions with varying degrees of bend. Tediousness and time consuming nature of the effort for ground truth creation makes it difficult to scale the ground truth for training phase. The present disclosure provides an end-to-end solution that reduces the cognitive burden of segmenting and karyotyping chromosomes. Dependency on experts is reduced by employing crowdsourcing while simultaneously addressing the issues associated with crowdsourcing. Identified segments through crowdsourcing are pre-processed to improve classification achieved by employing deep convolutional network (CNN).


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