US 12,169,933 B2
Severity quantification and lesion localization method of infectious disease on CXR using vision transformer and apparatus therefor
JongChul Ye, Daejeon (KR); Sangjoon Park, Daejeon (KR); and Gwanghyun Kim, Daejeon (KR)
Assigned to Korea Advanced Institute of Science and Technology, Daejeon (KR)
Filed by Korea Advanced Institute of Science and Technology, Daejeon (KR)
Filed on Mar. 25, 2022, as Appl. No. 17/704,879.
Claims priority of application No. 10-2021-0039509 (KR), filed on Mar. 26, 2021; and application No. 10-2021-0070757 (KR), filed on Jun. 1, 2021.
Prior Publication US 2022/0309661 A1, Sep. 29, 2022
Int. Cl. G06T 7/00 (2017.01); A61B 6/00 (2006.01); G06T 7/10 (2017.01); G06T 7/73 (2017.01); G06V 10/32 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01)
CPC G06T 7/0012 (2013.01) [A61B 6/5217 (2013.01); G06T 7/10 (2017.01); G06T 7/73 (2017.01); G06V 10/32 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06T 2207/10116 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30061 (2013.01); G06T 2207/30096 (2013.01)] 16 Claims
OG exemplary drawing
 
1. A method of quantifying severity of infectious disease based on a vision transformer, the method comprising:
receiving an input chest X-ray (CXR) image;
extracting a feature map from the received input CXR image using a pretrained neural network;
classifying a lesion in the input CXR image using the vision transformer based on the extracted feature map; and
quantifying severity of the input CXR image based on the extracted feature map and the classified lesion,
wherein the quantifying comprises quantifying the severity of the input CXR image based on a combination of information included in the extracted feature map and the classified lesion and localizing a position of the lesion.