JP7030050B2 - 組織パラメータ推定を用いたmrデータからの疑似ct生成 - Google Patents
組織パラメータ推定を用いたmrデータからの疑似ct生成 Download PDFInfo
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- JP7030050B2 JP7030050B2 JP2018519467A JP2018519467A JP7030050B2 JP 7030050 B2 JP7030050 B2 JP 7030050B2 JP 2018519467 A JP2018519467 A JP 2018519467A JP 2018519467 A JP2018519467 A JP 2018519467A JP 7030050 B2 JP7030050 B2 JP 7030050B2
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N5/00—Radiation therapy
- A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
- A61N5/103—Treatment planning systems
- A61N5/1039—Treatment planning systems using functional images, e.g. PET or MRI
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- A—HUMAN NECESSITIES
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
- A61B5/055—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R33/00—Arrangements or instruments for measuring magnetic variables
- G01R33/20—Arrangements or instruments for measuring magnetic variables involving magnetic resonance
- G01R33/44—Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
- G01R33/48—NMR imaging systems
- G01R33/4808—Multimodal MR, e.g. MR combined with positron emission tomography [PET], MR combined with ultrasound or MR combined with computed tomography [CT]
- G01R33/4812—MR combined with X-ray or computed tomography [CT]
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- G06N5/04—Inference or reasoning models
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- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
- A61B6/03—Computed tomography [CT]
- A61B6/032—Transmission computed tomography [CT]
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
- A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
- A61B6/5205—Devices using data or image processing specially adapted for radiation diagnosis involving processing of raw data to produce diagnostic data
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- G—PHYSICS
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10081—Computed x-ray tomography [CT]
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
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- G06T2207/10088—Magnetic resonance imaging [MRI]
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- General Physics & Mathematics (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
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- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Radiology & Medical Imaging (AREA)
- General Health & Medical Sciences (AREA)
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- Heart & Thoracic Surgery (AREA)
- Evolutionary Biology (AREA)
- Surgery (AREA)
- Pulmonology (AREA)
- Condensed Matter Physics & Semiconductors (AREA)
- Apparatus For Radiation Diagnosis (AREA)
- Magnetic Resonance Imaging Apparatus (AREA)
- Radiation-Therapy Devices (AREA)
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Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US14/881,939 | 2015-10-13 | ||
| US14/881,939 US10102451B2 (en) | 2015-10-13 | 2015-10-13 | Pseudo-CT generation from MR data using tissue parameter estimation |
| PCT/US2016/056635 WO2017066317A1 (en) | 2015-10-13 | 2016-10-12 | Pseudo-ct generation from mr data using tissue parameter estimation |
Related Child Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2020216068A Division JP2021049424A (ja) | 2015-10-13 | 2020-12-25 | 組織パラメータ推定を用いたmrデータからの疑似ct生成 |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2018535732A JP2018535732A (ja) | 2018-12-06 |
| JP2018535732A5 JP2018535732A5 (ja) | 2020-02-20 |
| JP7030050B2 true JP7030050B2 (ja) | 2022-03-04 |
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Family Applications (2)
| Application Number | Title | Priority Date | Filing Date |
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| JP2018519467A Active JP7030050B2 (ja) | 2015-10-13 | 2016-10-12 | 組織パラメータ推定を用いたmrデータからの疑似ct生成 |
| JP2020216068A Pending JP2021049424A (ja) | 2015-10-13 | 2020-12-25 | 組織パラメータ推定を用いたmrデータからの疑似ct生成 |
Family Applications After (1)
| Application Number | Title | Priority Date | Filing Date |
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| JP2020216068A Pending JP2021049424A (ja) | 2015-10-13 | 2020-12-25 | 組織パラメータ推定を用いたmrデータからの疑似ct生成 |
Country Status (7)
| Country | Link |
|---|---|
| US (2) | US10102451B2 (enExample) |
| EP (1) | EP3362146B1 (enExample) |
| JP (2) | JP7030050B2 (enExample) |
| CN (1) | CN108778416B (enExample) |
| AU (1) | AU2016339009B2 (enExample) |
| RU (1) | RU2018117507A (enExample) |
| WO (1) | WO2017066317A1 (enExample) |
Families Citing this family (45)
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| US10102451B2 (en) * | 2015-10-13 | 2018-10-16 | Elekta, Inc. | Pseudo-CT generation from MR data using tissue parameter estimation |
| JP6748207B2 (ja) * | 2015-12-18 | 2020-08-26 | コーニンクレッカ フィリップス エヌ ヴェKoninklijke Philips N.V. | 患者特有の局所的に変化するマージンを決定する方法 |
| WO2018085788A1 (en) * | 2016-11-04 | 2018-05-11 | The University Of North Carolina At Chapel Hill Office Of Commercialization And Economic Development | Methods, systems, and computer readable media for smart image protocoling |
| EP3441003B1 (en) | 2017-08-08 | 2020-07-22 | Siemens Healthcare GmbH | Method for performing digital subtraction angiography, hybrid imaging device, computer program and electronically readable storage medium |
| TWI637187B (zh) * | 2017-09-19 | 2018-10-01 | 臺北榮民總醫院 | 磁共振影像的分析方法及評估放射治療風險的方法 |
| US10803984B2 (en) | 2017-10-06 | 2020-10-13 | Canon Medical Systems Corporation | Medical image processing apparatus and medical image processing system |
| US11517197B2 (en) * | 2017-10-06 | 2022-12-06 | Canon Medical Systems Corporation | Apparatus and method for medical image reconstruction using deep learning for computed tomography (CT) image noise and artifacts reduction |
| JP6810675B2 (ja) * | 2017-11-16 | 2021-01-06 | 東京エレクトロンデバイス株式会社 | 情報処理装置及びプログラム |
| US10878529B2 (en) * | 2017-12-22 | 2020-12-29 | Canon Medical Systems Corporation | Registration method and apparatus |
| US11410086B2 (en) * | 2018-02-22 | 2022-08-09 | General Electric Company | System and method for class specific deep learning |
| EP3543911A1 (en) * | 2018-03-22 | 2019-09-25 | Koninklijke Philips N.V. | Anomaly detection using magnetic resonance fingerprinting |
| US10453224B1 (en) * | 2018-03-27 | 2019-10-22 | Ziwei Lin | Pseudo-CT generation with multi-variable regression of multiple MRI scans |
| US10657410B2 (en) * | 2018-04-13 | 2020-05-19 | Siemens Healthcare Gmbh | Method and system for abnormal tissue detection using z-scores in a joint histogram |
| EP3617733A1 (en) * | 2018-08-30 | 2020-03-04 | Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. | Method and apparatus for processing magnetic resonance data using machine learning |
| US10594027B1 (en) * | 2018-08-31 | 2020-03-17 | Hughes Networks Systems, Llc | Machine learning models for detecting the causes of conditions of a satellite communication system |
| US11978557B2 (en) * | 2018-09-12 | 2024-05-07 | Splink, Inc. | Diagnosis support system and method |
| WO2020082207A1 (en) * | 2018-10-22 | 2020-04-30 | Shanghai United Imaging Healthcare Co., Ltd. | Systems and methods for attenuation correction |
| CN109697741B (zh) * | 2018-12-28 | 2023-06-16 | 上海联影智能医疗科技有限公司 | 一种pet图像重建方法、装置、设备及介质 |
| CN109785405A (zh) * | 2019-01-29 | 2019-05-21 | 子威·林 | 利用多组磁共振图像的多变量回归生成准ct图像的方法 |
| JP7467145B2 (ja) * | 2019-02-08 | 2024-04-15 | キヤノンメディカルシステムズ株式会社 | 放射線治療計画装置 |
| JP7195961B2 (ja) * | 2019-02-08 | 2022-12-26 | キヤノンメディカルシステムズ株式会社 | 医用処理装置、x線ctシステム及び処理プログラム |
| CN109978965B (zh) * | 2019-03-21 | 2025-09-30 | 江南大学 | 一种模拟ct图像生成方法、装置、计算机设备和存储介质 |
| WO2020218967A1 (en) | 2019-04-26 | 2020-10-29 | Spectronic Ab | Generating synthetic electron density images from magnetic resonance images |
| CN110270015B (zh) * | 2019-05-08 | 2021-03-09 | 中国科学技术大学 | 一种基于多序列MRI的sCT生成方法 |
| EP3751579A1 (en) | 2019-06-13 | 2020-12-16 | RaySearch Laboratories AB | System and method for training a machine learning model and for providing an estimated interior image of a patient |
| US11531080B2 (en) * | 2019-07-24 | 2022-12-20 | Cypress Semiconductor Corporation | Leveraging spectral diversity for machine learning-based estimation of radio frequency signal parameters |
| JP7170897B2 (ja) | 2019-09-30 | 2022-11-14 | 富士フイルム株式会社 | 学習装置、方法およびプログラム、画像生成装置、方法およびプログラム、並びに画像生成モデル |
| US11282218B2 (en) * | 2019-11-25 | 2022-03-22 | Shanghai United Imaging Intelligence Co., Ltd. | Systems and methods for providing medical guidance using a patient depth image |
| US11838531B2 (en) * | 2019-12-06 | 2023-12-05 | Dolby Laboratories Licensing Corporation | Cascade prediction |
| US11348243B2 (en) | 2020-01-24 | 2022-05-31 | GE Precision Healthcare LLC | Systems and methods for medical image style transfer using deep neural networks |
| EP3882648B1 (en) | 2020-03-18 | 2024-09-25 | Siemens Healthineers AG | Rf coil device for an mr or mr-pet imaging modality and method to determine the position and/or orientation and/or shape of such an rf coil device |
| US11562482B2 (en) | 2020-03-30 | 2023-01-24 | Varian Medical Systems International Ag | Systems and methods for pseudo image data augmentation for training machine learning models |
| US11554496B2 (en) * | 2020-04-03 | 2023-01-17 | Fanuc Corporation | Feature detection by deep learning and vector field estimation |
| JP6989860B2 (ja) * | 2020-05-02 | 2022-01-12 | Arithmer株式会社 | 画像検査装置、画像検査方法及びプログラム |
| WO2021225640A1 (en) * | 2020-05-06 | 2021-11-11 | Siemens Medical Solutions Usa, Inc. | Systems and methods for low field mr/pet imaging |
| CN111626972B (zh) * | 2020-06-02 | 2023-06-02 | 上海鹰瞳医疗科技有限公司 | Ct图像重构方法、模型训练方法及设备 |
| JP7487096B2 (ja) * | 2020-12-24 | 2024-05-20 | パナソニック インテレクチュアル プロパティ コーポレーション オブ アメリカ | 制御システム及び制御方法 |
| EP4030179A1 (en) * | 2021-01-19 | 2022-07-20 | Koninklijke Philips N.V. | Method of predicting a field perturbation map for magnetic resonance imaging |
| KR102746259B1 (ko) * | 2021-03-11 | 2024-12-27 | 한국과학기술연구원 | 인공지능 기반 mri-ct 영상 변환 방법 및 이를 이용한 초음파 치료 장치 |
| CN113255756B (zh) * | 2021-05-20 | 2024-05-24 | 联仁健康医疗大数据科技股份有限公司 | 图像融合方法、装置、电子设备及存储介质 |
| CN114882996B (zh) * | 2022-03-17 | 2023-04-07 | 深圳大学 | 基于多任务学习的肝细胞癌ck19及mvi预测方法 |
| US20230377721A1 (en) * | 2022-05-19 | 2023-11-23 | Elekta Ltd. | Jointly trained machine learning models for automatic contouring in radiotherapy applications |
| US12107742B2 (en) | 2022-08-31 | 2024-10-01 | Hughes Network Systems, Llc | Machine learning to enhance satellite terminal performance |
| CN118154587A (zh) * | 2024-05-09 | 2024-06-07 | 四川省肿瘤医院 | 一种MRI-only放疗的质量控制方法 |
| CN118864288B (zh) * | 2024-09-25 | 2025-01-28 | 江西省肿瘤医院(江西省第二人民医院、江西省癌症中心) | 无监督伪ct对抗扩散模型构建方法、系统、介质及设备 |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US20110286649A1 (en) | 2010-05-20 | 2011-11-24 | Siemens Corporation | Generating pseudo-ct image volumes from ultra-short echo time mr |
| WO2013144799A1 (en) | 2012-03-29 | 2013-10-03 | Koninklijke Philips N.V. | Mri method for assigning individual pixels or voxels tissue - specific pet attenuation values |
| WO2015144540A1 (en) | 2014-03-28 | 2015-10-01 | Koninklijke Philips N.V. | Method and device for generating one or more computer tomography images based on magnetic resonance images with the help of tissue class separation |
| WO2015150065A1 (en) | 2014-04-01 | 2015-10-08 | Koninklijke Philips N.V. | A method estimating a pseudo hounsfield unit value |
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| US8787648B2 (en) * | 2008-03-07 | 2014-07-22 | Koninklijke Philips N.V. | CT surrogate by auto-segmentation of magnetic resonance images |
| US8218848B2 (en) * | 2008-07-23 | 2012-07-10 | Siemens Aktiengesellschaft | System and method for the generation of attenuation correction maps from MR images |
| US9135695B2 (en) * | 2012-04-04 | 2015-09-15 | Siemens Aktiengesellschaft | Method for creating attenuation correction maps for PET image reconstruction |
| US9392958B2 (en) * | 2012-05-30 | 2016-07-19 | Siemens Aktiengesellschaft | Method of attenuation correction of positron emission tomography data and combined positron emission tomography and magnetic resonance tomography system |
| FR2994481B1 (fr) * | 2012-08-07 | 2014-08-29 | Snecma | Procede de caracterisation d'un objet en materiau composite |
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| EP2991546B1 (en) | 2013-04-02 | 2016-11-30 | Koninklijke Philips N.V. | Detection of bone tissue using magnetic resonance imaging |
| WO2015081079A1 (en) | 2013-11-26 | 2015-06-04 | Henry Ford Innovation Institute | Software for using magnetic resonance images to generate a synthetic computed tomography image |
| US10029121B2 (en) | 2013-12-31 | 2018-07-24 | The Medical College Of Wisconsin, Inc. | System and method for producing synthetic images |
| US10307108B2 (en) * | 2015-10-13 | 2019-06-04 | Elekta, Inc. | Pseudo-CT generation from MR data using a feature regression model |
| US10102451B2 (en) * | 2015-10-13 | 2018-10-16 | Elekta, Inc. | Pseudo-CT generation from MR data using tissue parameter estimation |
-
2015
- 2015-10-13 US US14/881,939 patent/US10102451B2/en active Active
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2016
- 2016-10-12 RU RU2018117507A patent/RU2018117507A/ru not_active Application Discontinuation
- 2016-10-12 JP JP2018519467A patent/JP7030050B2/ja active Active
- 2016-10-12 AU AU2016339009A patent/AU2016339009B2/en active Active
- 2016-10-12 EP EP16784722.7A patent/EP3362146B1/en active Active
- 2016-10-12 CN CN201680072849.7A patent/CN108778416B/zh active Active
- 2016-10-12 WO PCT/US2016/056635 patent/WO2017066317A1/en not_active Ceased
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2018
- 2018-09-05 US US16/122,331 patent/US10664723B2/en active Active
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2020
- 2020-12-25 JP JP2020216068A patent/JP2021049424A/ja active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110286649A1 (en) | 2010-05-20 | 2011-11-24 | Siemens Corporation | Generating pseudo-ct image volumes from ultra-short echo time mr |
| WO2013144799A1 (en) | 2012-03-29 | 2013-10-03 | Koninklijke Philips N.V. | Mri method for assigning individual pixels or voxels tissue - specific pet attenuation values |
| WO2015144540A1 (en) | 2014-03-28 | 2015-10-01 | Koninklijke Philips N.V. | Method and device for generating one or more computer tomography images based on magnetic resonance images with the help of tissue class separation |
| WO2015150065A1 (en) | 2014-04-01 | 2015-10-08 | Koninklijke Philips N.V. | A method estimating a pseudo hounsfield unit value |
Non-Patent Citations (2)
| Title |
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| Adam Johansson et al.,"CT substitute derived from MRI sequences with ultrashort echo time",2011,Medical Physics,Vol.38,No.5,p.2708-2714 |
| Matthias Hofmann et al.,"MRI-Based Attenuation Correction for PET/MRI:A Novel Approach Combining Pattern Recognition and Atlas Registration",The Journal of Nuclear Medicine,2008,Vol.49,No.11,p.1875-1883 |
Also Published As
| Publication number | Publication date |
|---|---|
| US10664723B2 (en) | 2020-05-26 |
| RU2018117507A3 (enExample) | 2020-02-27 |
| AU2016339009A1 (en) | 2018-04-26 |
| WO2017066317A1 (en) | 2017-04-20 |
| RU2018117507A (ru) | 2019-11-14 |
| US20170103287A1 (en) | 2017-04-13 |
| CN108778416B (zh) | 2020-06-19 |
| CN108778416A (zh) | 2018-11-09 |
| JP2021049424A (ja) | 2021-04-01 |
| JP2018535732A (ja) | 2018-12-06 |
| US10102451B2 (en) | 2018-10-16 |
| EP3362146A1 (en) | 2018-08-22 |
| AU2016339009B2 (en) | 2020-02-06 |
| US20190042885A1 (en) | 2019-02-07 |
| EP3362146B1 (en) | 2020-03-25 |
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