CN116888624A - 通过机器学习的对比度提升 - Google Patents

通过机器学习的对比度提升 Download PDF

Info

Publication number
CN116888624A
CN116888624A CN202280015039.3A CN202280015039A CN116888624A CN 116888624 A CN116888624 A CN 116888624A CN 202280015039 A CN202280015039 A CN 202280015039A CN 116888624 A CN116888624 A CN 116888624A
Authority
CN
China
Prior art keywords
image
training
contrast
machine learning
images
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
CN202280015039.3A
Other languages
English (en)
Chinese (zh)
Inventor
L·戈申
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Koninklijke Philips NV
Original Assignee
Koninklijke Philips NV
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Koninklijke Philips NV filed Critical Koninklijke Philips NV
Publication of CN116888624A publication Critical patent/CN116888624A/zh
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/084Backpropagation, e.g. using gradient descent
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration
    • G06T5/60Image enhancement or restoration using machine learning, e.g. neural networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/045Combinations of networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/045Combinations of networks
    • G06N3/0455Auto-encoder networks; Encoder-decoder networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/0464Convolutional networks [CNN, ConvNet]
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/047Probabilistic or stochastic networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/0475Generative networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/0495Quantised networks; Sparse networks; Compressed networks
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/082Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/0895Weakly supervised learning, e.g. semi-supervised or self-supervised learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • G06N3/094Adversarial learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration
    • G06T5/70Denoising; Smoothing
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration
    • G06T5/90Dynamic range modification of images or parts thereof
    • G06T5/92Dynamic range modification of images or parts thereof based on global image properties
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration
    • G06T5/90Dynamic range modification of images or parts thereof
    • G06T5/94Dynamic range modification of images or parts thereof based on local image properties, e.g. for local contrast enhancement
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/048Activation functions
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10072Tomographic images
    • G06T2207/10081Computed x-ray tomography [CT]
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10072Tomographic images
    • G06T2207/10088Magnetic resonance imaging [MRI]
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10116X-ray image
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20081Training; Learning
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20084Artificial neural networks [ANN]
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Molecular Biology (AREA)
  • Artificial Intelligence (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Health & Medical Sciences (AREA)
  • Evolutionary Computation (AREA)
  • General Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Probability & Statistics with Applications (AREA)
  • Apparatus For Radiation Diagnosis (AREA)
  • Magnetic Resonance Imaging Apparatus (AREA)
  • Image Analysis (AREA)
CN202280015039.3A 2021-02-15 2022-02-14 通过机器学习的对比度提升 Pending CN116888624A (zh)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
EP21157112.0A EP4044109A1 (en) 2021-02-15 2021-02-15 Contrast boost by machine learning
EP21157112.0 2021-02-15
PCT/EP2022/053452 WO2022171845A1 (en) 2021-02-15 2022-02-14 Contrast boost by machine learning

Publications (1)

Publication Number Publication Date
CN116888624A true CN116888624A (zh) 2023-10-13

Family

ID=74625880

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202280015039.3A Pending CN116888624A (zh) 2021-02-15 2022-02-14 通过机器学习的对比度提升

Country Status (5)

Country Link
US (1) US12511718B2 (https=)
EP (2) EP4044109A1 (https=)
JP (1) JP2024507766A (https=)
CN (1) CN116888624A (https=)
WO (1) WO2022171845A1 (https=)

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2024251601A1 (de) * 2023-06-05 2024-12-12 Bayer Aktiengesellschaft Erzeugen von künstlichen kontrastverstärkten radiologischen aufnahmen
CN116759042B (zh) * 2023-08-22 2023-12-22 之江实验室 一种基于环形一致性的反事实医疗数据生成系统及方法
EP4567716A1 (en) * 2023-12-06 2025-06-11 Bayer Aktiengesellschaft Generating synthetic representations
WO2025137799A1 (en) * 2023-12-25 2025-07-03 Bracco Imaging S.P.A. Simulating images with higher contrast-enhancement in medical applications based on inverse problem
EP4614433A1 (en) * 2024-03-08 2025-09-10 Koninklijke Philips N.V. Synthesizing contrasted x-ray-based image data
JP2025178956A (ja) * 2024-05-27 2025-12-09 学校法人帝京大学 生成モデルの訓練方法、訓練装置、画像生成方法、画像生成装置およびプログラム
CN119991534B (zh) * 2025-04-14 2025-07-29 青岛瑞思德生物科技有限公司 医学图像低对比度区域自适应增强方法及系统

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3731144A1 (en) * 2019-04-25 2020-10-28 Koninklijke Philips N.V. Deep adversarial artifact removal
CN111915513A (zh) * 2020-07-10 2020-11-10 河海大学 一种基于改进的自适应神经网络的图像去噪方法
WO2020234051A1 (en) * 2019-05-17 2020-11-26 Koninklijke Philips N.V. Deep virtual contrast
CN112258438A (zh) * 2020-10-28 2021-01-22 清华大学深圳国际研究生院 一种基于非配对数据的ldct图像恢复算法

Family Cites Families (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US1028282A (en) 1911-06-21 1912-06-04 Arthur Horowitz Apparatus for producing vegetable extracts.
EP2504811B1 (en) 2009-11-25 2014-06-18 Koninklijke Philips N.V. Enhanced image data/dose reduction
WO2012073140A1 (en) 2010-12-01 2012-06-07 Koninklijke Philips Electronics N.V. Contrast to noise ratio (cnr) enhancer
JP6100772B2 (ja) 2011-07-15 2017-03-22 コーニンクレッカ フィリップス エヌ ヴェKoninklijke Philips N.V. 画像処理方法及びコンピューティング装置
JP6472088B2 (ja) 2013-02-21 2019-02-20 コーニンクレッカ フィリップス エヌ ヴェKoninklijke Philips N.V. スペクトルctに関する構造伝播復元
BR112020007105A2 (pt) 2017-10-09 2020-09-24 The Board Of Trustees Of The Leland Stanford Junior University método para treinar um dispositivo de diagnóstico por imagem para realizar uma imagem para diagnóstico médico com uma dose reduzida de agente de contraste
CN111699510A (zh) * 2018-02-12 2020-09-22 豪夫迈·罗氏有限公司 数字病理学图像的变换
US11501438B2 (en) * 2018-04-26 2022-11-15 Elekta, Inc. Cone-beam CT image enhancement using generative adversarial networks
US11222415B2 (en) 2018-04-26 2022-01-11 The Regents Of The University Of California Systems and methods for deep learning microscopy
EP3576050A1 (en) 2018-05-29 2019-12-04 Koninklijke Philips N.V. Deep anomaly detection
US11232541B2 (en) * 2018-10-08 2022-01-25 Rensselaer Polytechnic Institute CT super-resolution GAN constrained by the identical, residual and cycle learning ensemble (GAN-circle)
CN112703513B (zh) * 2019-03-04 2025-05-13 松下电器(美国)知识产权公司 信息处理方法及信息处理系统
US20200372301A1 (en) * 2019-05-21 2020-11-26 Retrace Labs Adversarial Defense Platform For Automated Dental Image Classification

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3731144A1 (en) * 2019-04-25 2020-10-28 Koninklijke Philips N.V. Deep adversarial artifact removal
WO2020234051A1 (en) * 2019-05-17 2020-11-26 Koninklijke Philips N.V. Deep virtual contrast
CN111915513A (zh) * 2020-07-10 2020-11-10 河海大学 一种基于改进的自适应神经网络的图像去噪方法
CN112258438A (zh) * 2020-10-28 2021-01-22 清华大学深圳国际研究生院 一种基于非配对数据的ldct图像恢复算法

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
ANONYMOUS: "A Gentle Introduction to CycleGAN for Image Translation", HTTPS://WEB.ARCHIVE.ORG/WEB/20210210102051/HTTPS://MACHINELEARNINGMASTERY.COM/WHAT-IS-CYCLEGAN/, 10 February 2021 (2021-02-10), pages 1 - 18 *

Also Published As

Publication number Publication date
EP4292043A1 (en) 2023-12-20
US12511718B2 (en) 2025-12-30
JP2024507766A (ja) 2024-02-21
US20240311974A1 (en) 2024-09-19
WO2022171845A1 (en) 2022-08-18
EP4044109A1 (en) 2022-08-17

Similar Documents

Publication Publication Date Title
CN116917945A (zh) 用于对比度增强机器学习系统的训练数据合成器
CN116888624A (zh) 通过机器学习的对比度提升
CN112969412B (zh) 深谱团注剂跟踪
CN111373448B (zh) 使用机器学习正则化器的图像重建
Würfl et al. Deep learning computed tomography: Learning projection-domain weights from image domain in limited angle problems
Chen et al. LEARN: Learned experts’ assessment-based reconstruction network for sparse-data CT
Gajera et al. CT-scan denoising using a charbonnier loss generative adversarial network
US12530745B2 (en) Systems and methods to reduce unstructured and structured noise in image data
Isola et al. Fully automatic nonrigid registration‐based local motion estimation for motion‐corrected iterative cardiac CT reconstruction
Cheng et al. Learned full-sampling reconstruction from incomplete data
JP7513487B2 (ja) 情報処理方法、医用画像診断装置及び情報処理システム
EP3739522A1 (en) Deep virtual contrast
CN116157826A (zh) 深度无监督的图像质量增强
Wu et al. Unsharp structure guided filtering for self-supervised low-dose CT imaging
EP3731144A1 (en) Deep adversarial artifact removal
Chan et al. An attention-based deep convolutional neural network for ultra-sparse-view CT reconstruction
Ikuta et al. A deep recurrent neural network with FISTA optimization for CT metal artifact reduction
Shi et al. Clinical Metadata Guided Limited-Angle CT Image Reconstruction
Xia et al. Synergizing physics/model-based and data-driven methods for low-dose ct
EP3667618A1 (en) Deep partial-angle coronary restoration
Xing Deep Learning Based CT Image Reconstruction
US20260030819A1 (en) Cone beam artifact reduction
Wang et al. An Iterative Algorithm for Unrolled Unsupervised PET Image Reconstruction
Yang et al. Trans ${^ 2} $-CBCT: A Dual-Transformer Framework for Sparse-View CBCT Reconstruction
Nagare Advanced Algorithms for X-ray CT Image Reconstruction and Processing

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination