JP2023094592A5 - - Google Patents

Info

Publication number
JP2023094592A5
JP2023094592A5 JP2022205153A JP2022205153A JP2023094592A5 JP 2023094592 A5 JP2023094592 A5 JP 2023094592A5 JP 2022205153 A JP2022205153 A JP 2022205153A JP 2022205153 A JP2022205153 A JP 2022205153A JP 2023094592 A5 JP2023094592 A5 JP 2023094592A5
Authority
JP
Japan
Prior art keywords
nuclear medicine
scatter
training
image
neural network
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
JP2022205153A
Other languages
English (en)
Japanese (ja)
Other versions
JP2023094592A (ja
Filing date
Publication date
Priority claimed from US17/682,738 external-priority patent/US12475613B2/en
Application filed filed Critical
Publication of JP2023094592A publication Critical patent/JP2023094592A/ja
Publication of JP2023094592A5 publication Critical patent/JP2023094592A5/ja
Pending legal-status Critical Current

Links

JP2022205153A 2021-12-23 2022-12-22 核医学診断装置、画像処理方法及びプログラム Pending JP2023094592A (ja)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US202163293395P 2021-12-23 2021-12-23
US63/293,395 2021-12-23
US17/682,738 US12475613B2 (en) 2021-12-23 2022-02-28 Scatter estimation for PET from image-based convolutional neural network
US17/682,738 2022-02-28

Publications (2)

Publication Number Publication Date
JP2023094592A JP2023094592A (ja) 2023-07-05
JP2023094592A5 true JP2023094592A5 (https=) 2025-12-25

Family

ID=86896947

Family Applications (1)

Application Number Title Priority Date Filing Date
JP2022205153A Pending JP2023094592A (ja) 2021-12-23 2022-12-22 核医学診断装置、画像処理方法及びプログラム

Country Status (2)

Country Link
US (1) US12475613B2 (https=)
JP (1) JP2023094592A (https=)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20250148662A1 (en) * 2023-11-06 2025-05-08 Siemens Medical Solutions Usa, Inc. Methods and apparatus for deep learning based image reconstruction
US12586278B2 (en) * 2024-03-20 2026-03-24 Siemens Medical Solutions Usa, Inc. AI-driven PET reconstruction from histoimage

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110782502B (zh) 2018-07-31 2023-11-03 通用电气公司 基于深度学习的pet散射估计系统和使用感知神经网络模型的方法
CN111325686B (zh) 2020-02-11 2021-03-30 之江实验室 一种基于深度学习的低剂量pet三维重建方法
US11633163B2 (en) * 2020-06-08 2023-04-25 GE Precision Healthcare LLC Systems and methods for a stationary CT imaging system
US11874411B2 (en) * 2020-09-23 2024-01-16 Siemens Medical Solutions Usa, Inc. Estimation of partially missing attenuation in time-of-flight positron emission tomography

Similar Documents

Publication Publication Date Title
CN112770838B (zh) 使用自关注深度学习进行图像增强的系统和方法
Nomura et al. Projection‐domain scatter correction for cone beam computed tomography using a residual convolutional neural network
CN109978778B (zh) 基于残差学习的卷积神经网络医学ct图像去噪方法
CN107545309B (zh) 使用深度生成机器学习模型的图像质量评分
US12165318B2 (en) Systems and methods for accurate and rapid positron emission tomography using deep learning
JP2021521993A5 (https=)
US11475535B2 (en) PET-CT registration for medical imaging
CN111627082A (zh) 基于滤波反投影算法和神经网络的pet图像重建方法
JP2022506395A (ja) 陽電子放出断層撮影（ｐｅｔ）のための人工知能（ａｉ）ベースの標準取込み値（ｓｕｖ）補正及び変動評価
WO2021041125A1 (en) Systems and methods for accurate and rapid positron emission tomography using deep learning
JP2023094592A5 (https=)
US20210330274A1 (en) Computer-implemented method, computer program, systems and x-ray facility for correction of x-ray image data with regard to noise effects
CN114494479A (zh) 利用神经网络对低剂量pet图像进行同时衰减校正、散射校正和去噪声的系统和方法
CN115272507A (zh) 一种基于条件生成对抗网络模型的低剂量spect图像重建方法
CN110415311A (zh) Pet图像重建方法、系统、可读存储介质和设备
JP7238134B2 (ja) Ｐｅｔ画像化中の自動的な動き補正
CN107810518A (zh) 利用相关噪声在图像上的边缘探测
CN112700506A (zh) 断层成像分析中的散射辐射的影响的量化
CN114862980A (zh) 散射校正方法、pet成像方法、装置、设备及存储介质
CN115082342A (zh) 一种基于教师-学生模型的低剂量spect图像去噪方法
CN120678454A (zh) 根据组织图像的ai驱动的pet重建
CN113469915A (zh) 一种基于去噪打分匹配网络的pet重建方法
CN105631908A (zh) 一种pet图像重建方法和装置
JP7520802B2 (ja) 放射線画像処理装置、放射線画像処理方法、画像処理装置、学習装置、学習データの生成方法、及びプログラム
CN115482193A (zh) 多扫描图像处理