JP2018530401A5 - - Google Patents
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- JP2018530401A5 JP2018530401A5 JP2018519442A JP2018519442A JP2018530401A5 JP 2018530401 A5 JP2018530401 A5 JP 2018530401A5 JP 2018519442 A JP2018519442 A JP 2018519442A JP 2018519442 A JP2018519442 A JP 2018519442A JP 2018530401 A5 JP2018530401 A5 JP 2018530401A5
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- 238000002591 computed tomography Methods 0.000 claims description 59
- 238000000034 method Methods 0.000 claims description 21
- 238000010801 machine learning Methods 0.000 claims 17
- 238000012935 Averaging Methods 0.000 claims 1
- 230000011218 segmentation Effects 0.000 claims 1
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US14/881,903 | 2015-10-13 | ||
| US14/881,903 US10307108B2 (en) | 2015-10-13 | 2015-10-13 | Pseudo-CT generation from MR data using a feature regression model |
| PCT/US2016/056538 WO2017066247A1 (en) | 2015-10-13 | 2016-10-12 | Pseudo-ct generation from mr data using a feature regression model |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2018530401A JP2018530401A (ja) | 2018-10-18 |
| JP2018530401A5 true JP2018530401A5 (cg-RX-API-DMAC7.html) | 2019-06-27 |
| JP6567179B2 JP6567179B2 (ja) | 2019-08-28 |
Family
ID=57227090
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2018519442A Active JP6567179B2 (ja) | 2015-10-13 | 2016-10-12 | 特徴回帰モデルを用いたｍｒデータからの疑似ｃｔ生成 |
Country Status (7)
| Country | Link |
|---|---|
| US (3) | US10307108B2 (cg-RX-API-DMAC7.html) |
| EP (2) | EP3362984B1 (cg-RX-API-DMAC7.html) |
| JP (1) | JP6567179B2 (cg-RX-API-DMAC7.html) |
| CN (1) | CN108770373B (cg-RX-API-DMAC7.html) |
| AU (1) | AU2016338923B2 (cg-RX-API-DMAC7.html) |
| RU (1) | RU2703344C1 (cg-RX-API-DMAC7.html) |
| WO (1) | WO2017066247A1 (cg-RX-API-DMAC7.html) |
Families Citing this family (40)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
| US10792515B2 (en) * | 2015-12-18 | 2020-10-06 | Koninklijke Philips N.V. | Method for determining a patient specific locally varying margin |
| US10741195B2 (en) * | 2016-02-15 | 2020-08-11 | Mitsubishi Electric Corporation | Sound signal enhancement device |
| US10794977B2 (en) * | 2016-06-23 | 2020-10-06 | Siemens Healthcare Gmbh | System and method for normalized reference database for MR images via autoencoders |
| JP6761128B2 (ja) * | 2016-09-06 | 2020-09-23 | エレクタ、インク.Elekta, Inc. | 合成医療画像を生成するためのニューラルネットワーク |
| US11478212B2 (en) * | 2017-02-16 | 2022-10-25 | Siemens Healthcare Gmbh | Method for controlling scanner by estimating patient internal anatomical structures from surface data using body-surface and organ-surface latent variables |
| WO2018220089A1 (en) | 2017-05-31 | 2018-12-06 | Koninklijke Philips N.V. | Machine learning on raw medical imaging data for clinical decision support |
| US11276208B2 (en) * | 2017-06-12 | 2022-03-15 | The Research Foundation For The State University Of New York | System, method and computer-accessible medium for ultralow dose computed tomography image reconstruction |
| US10753997B2 (en) * | 2017-08-10 | 2020-08-25 | Siemens Healthcare Gmbh | Image standardization using generative adversarial networks |
| CN108416846A (zh) * | 2018-03-16 | 2018-08-17 | 北京邮电大学 | 一种无标识三维注册算法 |
| EP3543911A1 (en) * | 2018-03-22 | 2019-09-25 | Koninklijke Philips N.V. | Anomaly detection using magnetic resonance fingerprinting |
| EP3583982A1 (en) * | 2018-06-18 | 2019-12-25 | Koninklijke Philips N.V. | Therapy planning device |
| 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 |
| EP3633622A1 (en) * | 2018-10-02 | 2020-04-08 | Koninklijke Philips N.V. | Generation of pseudo radiographic images from optical images |
| CN109710793B (zh) * | 2018-12-25 | 2021-08-17 | 科大讯飞股份有限公司 | 一种哈希参数确定方法、装置、设备及存储介质 |
| 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 |
| US10467504B1 (en) * | 2019-02-08 | 2019-11-05 | Adhark, Inc. | Systems, methods, and storage media for evaluating digital images |
| US11531840B2 (en) | 2019-02-08 | 2022-12-20 | Vizit Labs, Inc. | Systems, methods, and storage media for training a model for image evaluation |
| CN109918519A (zh) * | 2019-02-26 | 2019-06-21 | 重庆善功科技有限公司 | 一种面向海量延时摄影胚胎图像存储与查询的方法及系统 |
| 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 |
| CN109893784A (zh) * | 2019-04-19 | 2019-06-18 | 深圳先进技术研究院 | 一种实现超声穿颅聚焦的方法以及电子设备 |
| WO2020218967A1 (en) * | 2019-04-26 | 2020-10-29 | Spectronic Ab | Generating synthetic electron density images from magnetic resonance images |
| CN110084318B (zh) * | 2019-05-07 | 2020-10-02 | 哈尔滨理工大学 | 一种结合卷积神经网络和梯度提升树的图像识别方法 |
| 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 |
| JP7451293B2 (ja) * | 2019-06-13 | 2024-03-18 | キヤノンメディカルシステムズ株式会社 | 放射線治療システム |
| US11024034B2 (en) * | 2019-07-02 | 2021-06-01 | Acist Medical Systems, Inc. | Image segmentation confidence determination |
| GB2586791B (en) * | 2019-08-30 | 2022-11-16 | Elekta ltd | Pseudo-CT image generation |
| EP3828579A1 (en) * | 2019-11-28 | 2021-06-02 | Koninklijke Philips N.V. | Adaptive reconstruction of magnetic resonance images |
| 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 |
| US12008695B2 (en) * | 2020-09-25 | 2024-06-11 | GE Precision Healthcare LLC | Methods and systems for translating magnetic resonance images to pseudo computed tomography images |
| CN112435554B (zh) * | 2020-11-25 | 2022-04-12 | 皖南医学院 | 一种ct教学模拟系统及其控制方法 |
| CN112509022A (zh) * | 2020-12-17 | 2021-03-16 | 安徽埃克索医疗机器人有限公司 | 一种术前三维影像与术中透视图像的无标定物配准方法 |
| CN114692665B (zh) * | 2020-12-25 | 2024-05-24 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | 基于度量学习的辐射源开集个体识别方法 |
| US11966454B2 (en) * | 2021-10-28 | 2024-04-23 | Shanghai United Imaging Intelligence Co., Ltd. | Self-contrastive learning for image processing |
| CN114190889A (zh) * | 2021-11-19 | 2022-03-18 | 上海联影智能医疗科技有限公司 | 心电信号的分类方法、系统、电子设备及可读存储介质 |
| CN114638745B (zh) * | 2022-03-16 | 2023-08-18 | 江南大学 | 一种基于多借鉴信息的医学影像智能转换方法 |
| US20250345638A1 (en) * | 2022-05-01 | 2025-11-13 | The General Hospital Corporation | System for and method of planning and real-time navigation for transcranial focused ultrasound stimulation |
| US20240296527A1 (en) * | 2023-03-02 | 2024-09-05 | GE Precision Healthcare LLC | Reducing noise in ct images using synthetic data |
| CN120125505B (zh) * | 2025-01-27 | 2025-09-16 | 中国人民解放军总医院第四医学中心 | 一种基于roi-hu数据库构建骨骼预测模型的方法和应用 |
Family Cites Families (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1271570C (zh) * | 2004-06-17 | 2006-08-23 | 上海交通大学 | 核磁共振多谱图像分割方法 |
| CN101061490A (zh) * | 2004-11-19 | 2007-10-24 | 皇家飞利浦电子股份有限公司 | 利用支持向量机（svm）在计算机辅助检测（cad）中进行假阳性降低的系统和方法 |
| JP5337031B2 (ja) * | 2006-08-17 | 2013-11-06 | コーニンクレッカ フィリップス エヌ ヴェ | Ｃｔ画像取得 |
| US8068654B2 (en) * | 2007-02-02 | 2011-11-29 | Siemens Akteingesellschaft | Method and system for detection and registration of 3D objects using incremental parameter learning |
| US8787648B2 (en) * | 2008-03-07 | 2014-07-22 | Koninklijke Philips N.V. | CT surrogate by auto-segmentation of magnetic resonance images |
| CN102165454B (zh) * | 2008-09-29 | 2015-08-05 | 皇家飞利浦电子股份有限公司 | 用于提高计算机辅助诊断对图像处理不确定性的鲁棒性的方法 |
| DE102008058488B4 (de) * | 2008-11-21 | 2018-09-20 | Siemens Healthcare Gmbh | Verfahren und Vorrichtung zur Aufbereitung von kombinierten MR-Emissionstomographieaufnahmen |
| BR212012002342U2 (pt) * | 2009-08-06 | 2015-11-03 | Koninkl Philips Electronics Nv | método de geração de uma imagem de um objeto com o uso de um aparelho de imagens que ten um detector, aparelho de formação de imagens médicas adaptado para gerar uma imagem de um objeto, e, sistema de formação de imagens combinadas de raios x e spect |
| US8774482B2 (en) | 2010-05-20 | 2014-07-08 | Siemens Aktiengesellschaft | Generating pseudo-CT image volumes from ultra-short echo time MR |
| US8706668B2 (en) * | 2010-06-02 | 2014-04-22 | Nec Laboratories America, Inc. | Feature set embedding for incomplete data |
| WO2013049818A1 (en) * | 2011-09-30 | 2013-04-04 | Cincinnati Children's Hospital Medical Center | Method for consistent and verifiable optimization of computed tomography (ct) radiation dose |
| US9256965B2 (en) * | 2013-01-30 | 2016-02-09 | Impac Medical Systems, Inc. | Method and apparatus for generating a derived image using images of different types |
| CN105263407B (zh) * | 2013-04-02 | 2018-09-14 | 皇家飞利浦有限公司 | 使用磁共振成像的对骨组织的探测 |
| US9235781B2 (en) * | 2013-08-09 | 2016-01-12 | Kabushiki Kaisha Toshiba | Method of, and apparatus for, landmark location |
| US10307108B2 (en) | 2015-10-13 | 2019-06-04 | Elekta, Inc. | Pseudo-CT generation from MR data using a feature regression model |
| JP7027416B2 (ja) | 2016-10-26 | 2022-03-01 | ナイキ イノベイト シーブイ | 自動履物プラットフォーム用の変形可能な締めひもガイド |
| KR102125361B1 (ko) | 2017-03-15 | 2020-06-22 | 나이키 이노베이트 씨.브이. | 케이블 및 갑피 텐셔너를 구비하는 자동화된 신발 |
-
2015
- 2015-10-13 US US14/881,903 patent/US10307108B2/en active Active
-
2016
- 2016-10-12 EP EP16790780.7A patent/EP3362984B1/en active Active
- 2016-10-12 AU AU2016338923A patent/AU2016338923B2/en active Active
- 2016-10-12 WO PCT/US2016/056538 patent/WO2017066247A1/en not_active Ceased
- 2016-10-12 EP EP21191291.0A patent/EP3940624B1/en active Active
- 2016-10-12 JP JP2018519442A patent/JP6567179B2/ja active Active
- 2016-10-12 CN CN201680072831.7A patent/CN108770373B/zh active Active
- 2016-10-12 RU RU2018117510A patent/RU2703344C1/ru active
-
2019
- 2019-03-15 US US16/354,495 patent/US11234654B2/en active Active
-
2021
- 2021-11-24 US US17/456,513 patent/US11944463B2/en active Active
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