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Title:
TRAINED MODEL GENERATION PROGRAM, IMAGE GENERATION PROGRAM, TRAINED MODEL GENERATION DEVICE, IMAGE GENERATION DEVICE, TRAINED MODEL GENERATION METHOD, AND IMAGE GENERATION METHOD
Document Type and Number:
WIPO Patent Application WO/2021/182103
Kind Code:
A1
Abstract:
This trained model generation program causes a computer to implement: a learning execution function for inputting, to a machine learning device, first input image data indicating a first input image generated by a first reconstruction method using compressed sensing, and second input image data indicating a second input image generated by a second reconstruction method that is different from the first reconstruction method and is an analytical reconstruction method, and causing the machine learning device to execute machine learning and generate a trained model; and a trained model acquisition function for acquiring trained model data indicating the trained model. Input image data indicating an input image is inputted to the trained model, and a reconstructed image that has improved image quality is generated.

Inventors:
KUDO HIROYUKI (JP)
MORI KAZUKI (JP)
Application Number:
PCT/JP2021/006833
Publication Date:
September 16, 2021
Filing Date:
February 24, 2021
Export Citation:
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Assignee:
UNIV TSUKUBA (JP)
International Classes:
A61B6/03
Domestic Patent References:
WO2016033458A12016-03-03
Foreign References:
US20190353741A12019-11-21
US20190371018A12019-12-05
US20190325621A12019-10-24
Other References:
HAN YO SEOB, YOO JAEJUN, YE JONG CHUL: "Deep residual learning for compressed sensing CT reconstruction via persistent homology analysis", ARXIV: 1611.06391V2, 25 November 2016 (2016-11-25), pages 1 - 10, XP080733245, Retrieved from the Internet [retrieved on 20210408]
MA, G. Y. ET AL.: "Low dose CT reconstruction assisted by an image manifold prior", ARXIV: 1810.12255, 29 October 2018 (2018-10-29), pages 1 - 15, XP081071090, Retrieved from the Internet [retrieved on 20210408]
Attorney, Agent or Firm:
TANAI Sumio et al. (JP)
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