US 12,288,328 B2
Blood flow field estimation apparatus, learning apparatus, blood flow field estimation method, and program
Hitomi Anzai, Sendai (JP); Kazuhiro Watanabe, Sendai (JP); Gaoyang Li, Sendai (JP); Makoto Ohta, Sendai (JP); Teiji Tominaga, Sendai (JP); Kuniyasu Niizuma, Sendai (JP); and Shinichiro Sugiyama, Sendai (JP)
Assigned to TOHOKU UNIVERSITY, Sendai (JP)
Appl. No. 17/798,870
Filed by TOHOKU UNIVERSITY, Sendai (JP)
PCT Filed Feb. 22, 2021, PCT No. PCT/JP2021/006654
§ 371(c)(1), (2) Date Aug. 10, 2022,
PCT Pub. No. WO2021/172280, PCT Pub. Date Sep. 2, 2021.
Claims priority of application No. 2020-033293 (JP), filed on Feb. 28, 2020.
Prior Publication US 2023/0046302 A1, Feb. 16, 2023
Int. Cl. G06T 7/187 (2017.01); A61B 5/02 (2006.01); A61B 5/0205 (2006.01); A61B 5/026 (2006.01); G06T 7/00 (2017.01)
CPC G06T 7/0012 (2013.01) [G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] 6 Claims
OG exemplary drawing
 
1. A blood flow field estimation apparatus, comprising:
a processor; and
a storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by the processor, perform:
by using a learned model obtained in advance by performing machine learning to learn a relationship between organ tissue three-dimensional structure data including image data of a plurality of organ cross-sectional images serving as cross-sectional images of an organ and having each pixel provided with two or more bit depths and image position information serving as information indicating a position of an image reflected on each of the organ cross-sectional images in the organ, and a blood flow field in the organ, estimating the blood flow field in the organ of an estimation target, based on the organ tissue three-dimensional structure data of the organ of the estimation target;
outputting an estimation result of the estimation,
dividing the organ tissue three-dimensional structure data into a plurality of partial data serving as data satisfying a partial condition; and
estimating the blood flow field in the organ of the estimation target by using the learned model for each of the partial data,
wherein the partial condition includes a condition that the partial data is partial information of the organ tissue three-dimensional structure data, a condition that the partial data indicates a pixel value at each position of a partial space in the organ out of pixel values indicated by the organ tissue three-dimensional structure data, and a condition that information indicated by a sum of all of the divided partial data is the same as information indicated by the organ tissue three-dimensional structure data.