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:
Sep. 22, 2020

Filed:

Oct. 12, 2018
Applicant:

Beijing Keya Medical Technology Co., Ltd., Beijing, CN;

Inventors:

Hanbo Chen, Seattle, WA (US);

Shanhui Sun, Princeton, NJ (US);

Youbing Yin, Kenmore, WA (US);

Qi Song, Seattle, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/11 (2017.01); G06T 7/136 (2017.01); G06N 3/08 (2006.01); G06T 7/12 (2017.01);
U.S. Cl.
CPC ...
G06T 7/11 (2017.01); G06N 3/08 (2013.01); G06T 7/12 (2017.01); G06T 7/136 (2017.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30004 (2013.01);
Abstract

Embodiments of the disclosure provide systems and methods for segmenting a medical image. An exemplary system includes a communication interface configured to receive the medical image acquired by an image acquisition device. The system further includes a memory configured to store a multi-level learning network including at least a first convolution block and a second convolution block. The second convolution block has at least one convolution layer. The system also includes a processor. The processor is configured to determine a first feature map by applying the first convolution block to the medical image, and determine a second feature map by applying the second convolution block to the first feature map. The processor is further configured to determine a first level feature map by concatenating the first feature map and the second feature map. The processor is also configured to obtain a first level segmented image based on the first level feature map.


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