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. 25, 2023

Filed:

Aug. 02, 2018
Applicant:

Boe Technology Group Co., Ltd., Beijing, CN;

Inventors:

Yingying Li, Beijing, CN;

Lvwei Wang, Beijing, CN;

Assignee:
Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 10/32 (2022.01); G06K 9/62 (2022.01); G06T 7/00 (2017.01); G06V 10/25 (2022.01);
U.S. Cl.
CPC ...
G06V 10/32 (2022.01); G06K 9/627 (2013.01); G06K 9/6256 (2013.01); G06K 9/6267 (2013.01); G06T 7/0012 (2013.01); G06V 10/25 (2022.01); G06T 2207/10024 (2013.01); G06T 2207/10056 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10104 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/20016 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20132 (2013.01); G06T 2207/30088 (2013.01); G06T 2207/30096 (2013.01); G06V 2201/03 (2022.01);
Abstract

The present disclosure provides a training method and device of a neural network for medical image processing, a medical image processing method and device, and an electronic apparatus for medical image processing based on a neural network. The training method includes performing a pre-processing process on an original image to obtain a pre-processed image, performing a data-augmenting process on the pre-processed image to obtain an augmented image retaining a pathological feature, the augmented image including at least one image with first resolution and at least one image with second resolution being higher than the first resolution, and training the neural network by selecting the image with first resolution and a part-cropping image from the image with second resolution as training samples.


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