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Determining a confidence indication for deep-learning image reconstruction in computed tomography
KTH, School of Engineering Sciences (SCI), Physics, Particle Physics, Astrophysics and Medical Imaging.ORCID iD: 0000-0002-5092-8822
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematics (Div.).ORCID iD: 0000-0001-8969-4253
KTH, School of Engineering Sciences (SCI), Physics, Particle Physics, Astrophysics and Medical Imaging.ORCID iD: 0000-0002-3039-9791
2025 (English)Patent (Other (popular science, discussion, etc.))
Abstract [ja]

コンピュータ断層撮影(CT)における機械学習画像再構成のための1つ以上の信頼度表示を決定するための方法及びシステムが提供される。この方法は、(S1)エネルギー分解X線データを取得することと、(S2)少なくとも1つの機械学習システムに基づいてエネルギー分解X線データを処理して、少なくとも1つの再構成基底画像又はその画像特徴の事後確率分布の表現を生成することとを備える。本方法は更に、事後確率分布の表現に基づいて、前記少なくとも1つの再構成基底画像、又は前記少なくとも1つの再構成基底画像に由来する少なくとも1つの派生画像、又は前記少なくとも1つの再構成基底画像又は前記少なくとも1つの派生画像の画像特徴に対する1つ以上の信頼度表示を生成する(S3)ことを含む。【選択図】図6A

Place, publisher, year, edition, pages
2025.
National Category
Medical Imaging
Identifiers
URN: urn:nbn:se:kth:diva-367953OAI: oai:DiVA.org:kth-367953DiVA, id: diva2:1986512
Patent
Japanese patent 7702611 (2025-07-04)
Note

The correct spelling of the inventor's name is Eguizabal.

QC 20250820

Available from: 2025-07-31 Created: 2025-07-31 Last updated: 2025-08-20Bibliographically approved

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Persson, MatsEguizabal, AlmaDanielsson, Mats

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