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. 07, 2022

Filed:

Feb. 12, 2020
Applicant:

Hon Hai Precision Industry Co., Ltd., New Taipei, TW;

Inventors:

Tzu-Chen Lin, New Taipei, TW;

Chin-Pin Kuo, New Taipei, TW;

Tung-Tso Tsai, New Taipei, TW;

Guo-Chin Sun, New Taipei, TW;

I-Hua Chen, New Taipei, TW;

Wan-Jhen Lee, New Taipei, TW;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); G06T 7/00 (2017.01); G06T 7/11 (2017.01); G06T 7/223 (2017.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06T 7/11 (2017.01); G06T 7/223 (2017.01); G06T 2207/10024 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20112 (2013.01); G06T 2207/20221 (2013.01); G06T 2207/30096 (2013.01);
Abstract

A method for detecting a tumor from images which are required to be shrunken in resolution obtains one or more first images. Then, the method segments or divides the detection images into a number of detection image blocks according to an input size of training data of a convolutional neural network architecture, before segmenting, each of the plurality of detection image blocks comprising coordinate values. The detection image blocks are input into a preset tumor detection model to generate image blocks of a result of the detection images. The method merges the image blocks into a single image according to the coordinate values of each detection image block. Colors of normal areas, abnormal areas, and overlapping areas of the abnormal areas are all different. The method generates a final detection according to color depths in the image. A tumor detection device and a non-transitory storage medium are provided.


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