US 12,236,585 B2
Method for measuring lesion of medical image
Yeong Won Kim, Seoul (KR); Kyungdoc Kim, Seoul (KR); Hong Seok Lee, Seoul (KR); and Hyeongsub Kim, Seoul (KR)
Assigned to VUNO Inc., Seoul (KR)
Filed by VUNO Inc., Seoul (KR)
Filed on Jan. 24, 2022, as Appl. No. 17/582,717.
Claims priority of application No. 10-2021-0011021 (KR), filed on Jan. 26, 2021; and application No. 10-2022-0003788 (KR), filed on Jan. 11, 2022.
Prior Publication US 2022/0237777 A1, Jul. 28, 2022
Int. Cl. G06T 7/00 (2017.01); G06V 10/40 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); A61B 6/00 (2006.01)
CPC G06T 7/0012 (2013.01) [G06V 10/40 (2022.01); G06V 10/774 (2022.01); G06V 10/776 (2022.01); G06V 10/82 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); A61B 6/5217 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30081 (2013.01); G06T 2207/30096 (2013.01); G06V 2201/03 (2022.01)] 12 Claims
OG exemplary drawing
 
1. A method of analyzing a lesion based on a medical image performed by a computing device including at least one processor, the method comprising:
extracting, by using a pre-trained artificial neural network, a first feature for each tile of a plurality of tiles included in an input image; and
extracting, by using the pre-trained artificial neural network, a second feature for an entirety of the input image, based on both information about whether the lesion is present for the each tile and information on a pattern of the lesion for the each tile generated based on first features of the plurality of tiles.