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1. 发明申请

WO2015092622A2 DENSITY GUIDED ATTENUATION MAP GENERATION IN PET/MR SYSTEMS 审中-公开
标题翻译： PET / MR系统中的密度指导衰减图生成
公开(公告)号：WO2015092622A2
公开(公告)日：2015-06-25
申请号：PCT/IB2014/066765
申请日：2014-12-10
申请人： KONINKLIJKE PHILIPS N.V.
发明人： BERKER, Yannick , DWIVEDI, Shekhar , SCHULZ, Volkmar , SHAO, Lingxiong
IPC分类号： G01R33/48
CPC分类号： G01R33/56509 , A61B5/0035 , A61B5/055 , G01R33/481 , G01R33/4816 , G01R33/4835 , G01R33/50 , G01R33/5608 , G01T1/1603 , G01T1/1647 , G06T7/11 , G06T7/136 , G06T2207/10088 , G06T2207/20132 , G06T2207/30061
摘要： A lung segmentation processor (40) is configured to classify magnetic resonance (MR) images based on noise characteristics. The MR segmenatation processor generates a lung region of interest (ROI) and detailed structure segmentation of the lung from the ROI. The MR segmentation processor performs an iterative normalization and region definition approach that captures the entire lung and the soft tissues within the lung accurately. Accuracy of the segmentation relies on artifact classification coming inherently from MR images. The MR segmentation processor (40) correlates segmented lung internal tissue pixels with the lung density to determine the attenuation coefficients based on the correlation. Lung densities are computed using MR data obtained from imaging sequences that minimize echo and acquisition times. The densities differentiate healthy tissues and lesions, which an attenuation map processor (36) uses to create localized attenuation maps for the lung.
摘要翻译：肺分割处理器（40）被配置为基于噪声特性对磁共振（MR）图像进行分类。 MR分割处理器生成感兴趣的肺部区域（ROI）和来自ROI的肺的详细结构分割。 MR分段处理器执行迭代归一化和区域定义方法，准确地捕获肺内整个肺和软组织。分割的准确性依赖于来自MR图像的固有的伪影分类。 MR分割处理器（40）将分割的肺内部组织像素与肺密度相关联，以基于相关性来确定衰减系数。使用从使回波和采集时间最小化的成像序列获得的MR数据计算肺密度。密度区分健康组织和病变，衰减图处理器（36）用于为肺创建局部衰减图。

2. 发明申请

WO2019134871A1 LEARNING-BASED VOXEL EVOLUTION FOR REGULARIZED RECONSTRUCTION 审中-公开
公开(公告)号：WO2019134871A1
公开(公告)日：2019-07-11
申请号：PCT/EP2018/086838
申请日：2018-12-24
申请人： KONINKLIJKE PHILIPS N.V.
发明人： DWIVEDI, Shekhar , BAI, Chuanyong , ANDREYEV, Andriy , ZHANG, Bin , HU, Zhiqiang
IPC分类号： G06T11/00
CPC分类号： G06T11/006 , G06T11/00 , G06T2207/10072 , G06T2211/424
摘要： A non-transitory computer-readable medium stores instructions readable and executable by at least one electronic processor (20) to perform an image reconstruction method (100). The method includes: performing iterative image reconstruction of imaging data acquired using an image acquisition device (12); selecting an update image from a plurality of update images produced by the iterative image reconstruction; processing the selected update image to generate a hot spot artifact map; and suppressing hot spots identified by the generated hot spot artifact map in a reconstructed image output by the iterative image reconstruction.

3. 发明申请

WO2019134905A1 IMAGE RECONSTRUCTION EMPLOYING TAILORED EDGE PRESERVING REGULARIZATION 审中-公开
公开(公告)号：WO2019134905A1
公开(公告)日：2019-07-11
申请号：PCT/EP2019/050017
申请日：2019-01-02
申请人： KONINKLIJKE PHILIPS N.V.
发明人： BAI, Chuanyong , ANDREYEV, Andriy , ZHANG, Bin , GURIAN, James , HU, Zhiqiang , HSIEH, Yu-Lung , DWIVEDI, Shekhar , YE, Jinghan , SONG, Xiyun , MILLER, Michael Allen
IPC分类号： G06T11/00
CPC分类号： G06T11/006 , G06T11/00 , G06T2211/424
摘要： A non-transitory computer-readable medium stores instructions readable and executable by a workstation (18) including at least one electronic processor (20) to perform an image reconstruction method (100). The method includes: determining a weighting parameter ( β ) of an edge-preserving regularization or penalty of a regularized image reconstruction of an image acquisition device (12) for an imaging data set obtained by the image acquisition device; determining an edge sensitivity parameter ( y ) of the edge -preserving algorithm for the imaging data set obtained by the image acquisition device; and reconstructing the imaging data set obtained by the image acquisition device to generate a reconstructed image by applying the regularized image reconstruction including the edge-preserving regularization or penalty with the determined weighting and edge sensitivity parameters to the imaging data set obtained by the image acquisition device.

4. 发明申请

WO2018099772A1 INTERACTIVE TARGETED ULTRAFAST RECONSTRUCTION IN EMISSION AND TRANSMISSION TOMOGRAPHY 审中-公开
公开(公告)号：WO2018099772A1
公开(公告)日：2018-06-07
申请号：PCT/EP2017/079987
申请日：2017-11-22
申请人： KONINKLIJKE PHILIPS N.V.
发明人： DWIVEDI, Shekhar , ANDREYEV, Andriy , BAI, Chuanyong , TUNG, Chi-Hua
IPC分类号： G06T11/00
摘要： An imaging data set (22) comprising detected counts along lines of response (LORs) is reconstructed (24) to generate a full-volume image at a standard resolution. A region selection graphical user interface (GUI) (26) is provided via which a user-chosen region of interest (ROI) is defined in the full-volume image, and this is automatically adjusted by identifying an anatomical feature corresponding to the user-chosen ROI and adjusting the user-chosen ROI to improve alignment with that feature. A sub-set (32) of the counts of the imaging data set is selected (30) for reconstructing the ROI, and only the selected sub-set is reconstructed (34) to generate a ROI image (36) representing the ROI at a higher resolution than the standard resolution. A fraction of the sub-set of counts may be reconstructed using different reconstruction algorithms (40) to generate corresponding sample ROI images, and a reconstruction algorithm selection graphical user interface (42) employs these sample ROI images.

5. 发明申请

WO2016009309A1 IRECON: INTELLIGENT IMAGE RECONSTRUCTION SYSTEM WITH ANTICIPATORY EXECUTION 审中-公开
标题翻译： IRECON：智能图像重建系统与安全执行
公开(公告)号：WO2016009309A1
公开(公告)日：2016-01-21
申请号：PCT/IB2015/055182
申请日：2015-07-09
申请人： KONINKLIJKE PHILIPS N.V.
发明人： TUNG, Chi-Hua , DWIVEDI, Shekhar , ZHU, Yang-Ming , COLLINS, John Patrick
IPC分类号： G06F19/00
CPC分类号： G06T11/003 , G06F3/04842 , G06F19/00 , G06F19/321 , G06T2210/41 , G16H40/63
摘要： A diagnostic imaging system retrieves data (206) from a plurality of accessible data sources, the accessible data sources storing data including physiological data describing a subject to be imaged, a nature of a requested diagnostic image, image preferences of a clinician who requested the diagnostic image, and previously reconstructed images of the requested nature of the subject and/or other subjects, reconstruction parameters and/or sub- routines used to reconstruct the previously reconstructed images. The system analyzes (6, 12) the retrieved data to automatically generate reconstruction parameters and/or sub-steps specific to the nature of the requested diagnostic image, the subject,and the clinician image preferences. The system controls a display device (10, 216) to display the generated reconstruction parameters and/or sub-routines to the user for a user selection. The system sets a reconstruction processor system to reconstruct scan data using the selected reconstruction parameters and/or sub-routines.
摘要翻译：诊断成像系统从多个可访问的数据源检索数据（206），所述可访问的数据源存储包括描述要成像的对象的生理数据的数据，所请求的诊断图像的性质，请求诊断的临床医生的图像偏好图像和先前重建的被摄体和/或其他对象的性质的重建图像，用于重构先前重建的图像的重建参数和/或子例程。系统分析（6,12）所检索的数据以自动生成针对所请求的诊断图像，受试者和临床医师图像偏好特有的重建参数和/或子步骤。系统控制显示设备（10,216），以便为用户选择显示生成的重建参数和/或子例程给用户。该系统设置重建处理器系统以使用所选择的重建参数和/或子例程来重构扫描数据。

6. 发明申请

WO2014057383A2 MULTI-STRUCTURE ATLAS AND/OR USE THEREOF 审中-公开
标题翻译：多结构地图和/或使用它们
公开(公告)号：WO2014057383A2
公开(公告)日：2014-04-17
申请号：PCT/IB2013/058912
申请日：2013-09-27
申请人： KONINKLIJKE PHILIPS N.V.
发明人： DWIVEDI, Shekhar
IPC分类号： G06T7/00
CPC分类号： G06T11/005 , G06K9/46 , G06K9/4604 , G06K2009/4666 , G06T7/0012 , G06T7/11 , G06T2207/10072 , G06T2207/20104 , G06T2207/20128 , G06T2207/30008 , G06T2207/30061
摘要： An image data processor (106) includes a structural image data processor (114) that employs a multi-structure atlas to segment a region of interest from structural image data that includes tissue of interest and that segments the tissue of interests from the region of interest. The image data processor further includes functional image data processor (116) that identifies the tissue of interest in functional image data based on the segmented tissue of interest. An image data processor includes a multi-structure atlas generator (104) that generates a multi-structure atlas. The multi-structure atlas physically maps structure to tissue of interest such that locate the structure in structural image data based on the multi- structure atlas localizes the tissue of interest to the region of interest.
摘要翻译：图像数据处理器（106）包括结构图像数据处理器（114），该结构图像数据处理器使用多结构图谱来从包括感兴趣组织的结构图像数据分割感兴趣区域，来自感兴趣区域的兴趣组织。图像数据处理器还包括基于分割的感兴趣组织识别功能图像数据中的感兴趣组织的功能图像数据处理器（116）。图像数据处理器包括生成多结构图集的多结构图集生成器（104）。多结构图谱将结构物理地映射到感兴趣组织，使得基于多结构图谱将结构定位在结构图像数据中，将感兴趣组织定位到感兴趣区域。

7. 发明申请

WO2018202648A1 GENERATION OF ACCURATE HYBRID DATASETS FOR QUANTITATIVE MOLECULAR IMAGING 审中-公开
公开(公告)号：WO2018202648A1
公开(公告)日：2018-11-08
申请号：PCT/EP2018/061083
申请日：2018-05-01
申请人： KONINKLIJKE PHILIPS N.V.
发明人： BAI, Chuanyong , ANDREYEV, Andriy , SONG, Xiyun , YE, Jinghan , ZHANG, Bin , DWIVEDI, Shekhar , MAO, Yanfei , HU, Zhiqiang
IPC分类号： G06T11/00
摘要： A non-transitory computer readable medium storing instructions readable and executable by an imaging workstation (14) including at least one electronic processor (16) to perform a dataset generation method (100) operating on emission imaging data acquired of a patient for one or more axial frames at a corresponding one or more bed positions, the method comprising: (a) identifying a frame of interest from the one or more axial frames; (b) generating simulated lesion data by simulating emission imaging data for the frame of interest of at least one simulated lesion placed in the frame of interest; (c) generating simulated frame emission imaging data by simulating emission imaging data for the frame of interest of the patient; (d) determining a normalization factor comprising a ratio of the value of a quantitative metric for the simulated patient data and the value of the quantitative metric for the emission imaging data acquired of the same patient for the frame of interest; and (e) generating a hybrid data set comprising the emission imaging data acquired of the patient for the one or more axial frames at the corresponding one or more bed positions with the frame of interest replaced by a combination of the simulated lesion data scaled by the normalization factor and the emission imaging data acquired of the patient for the frame of interest.

8. 发明申请

WO2016063211A1 CLASSIFIED TRUNCATION COMPENSATION 审中-公开
标题翻译：分类交叉补偿
公开(公告)号：WO2016063211A1
公开(公告)日：2016-04-28
申请号：PCT/IB2015/058063
申请日：2015-10-20
申请人： KONINKLIJKE PHILIPS N.V.
发明人： DWIVEDI, Shekhar
IPC分类号： G06T7/00 , G06K9/00 , G06T5/00
CPC分类号： G06T5/001 , G06K9/6267 , G06K2209/05 , G06T5/005 , G06T5/50 , G06T7/11 , G06T7/174 , G06T11/008 , G06T2207/10088 , G06T2207/10104 , G06T2207/20152 , G06T2207/20224 , G06T2211/432
摘要： PET/MR images are compensated with simplified adaptive algorithms for truncated parts of the body. The compensation adapts to a specific location of truncation of the body or organ in the MR image, and to attributes of the truncation in the truncated body part. Anatomical structures in a PET image that do not require any compensation are masked using a MR image with a smaller field of view. The organs that are not masked are then classified as types of anatomical structures, the orientation of the anatomical structures, and type of truncation. Structure specific algorithms are used to compensate for a truncated anatomical structure. The compensation is validated for correctness and the ROI is filled in where there is missing voxel data. Attenuation maps are generated from the compensated ROI.
摘要翻译： PET / MR图像用身体截肢部分的简化自适应算法进行补偿。补偿适应于MR图像中身体或器官的截断的特定位置，以及截短身体部位的截断属性。不需要任何补偿的PET图像中的解剖结构使用具有较小视野的MR图像进行掩蔽。然后将未掩盖的器官分类为解剖结构的类型，解剖结构的取向和截断的类型。结构特定的算法用于补偿截肢的解剖结构。验证补偿的正确性，并且ROI被填充在缺少体素数据的位置。从补偿的ROI生成衰减图。

9. 发明申请

WO2012153231A9 MYOCARDIAL CLUSTERIFICATION AND ORIENTATION 审中-公开
公开(公告)号：WO2012153231A9
公开(公告)日：2012-11-15
申请号：PCT/IB2012/052183
申请日：2012-05-02
申请人： KONINKLIJKE PHILIPS N.V. , DWIVEDI, Shekhar
发明人： DWIVEDI, Shekhar
IPC分类号： G06T7/00
摘要： A cardiac imaging method includes acquiring a projection image representation which includes a myocardium (SI 00). The myocardium is segmented and a mask is generated (SI 02). The mask is optimized (SI 04). A blood pool is determined from the optimized mask (SI 06) and the mask is skeletonized based on a clusterfication of the myocardial slices (S108). The center of mass is determined (SI 10) from the blood pool and the skeletonized mask. Myocardial parameters are determined (SI 12) from the skeletonized mask.

10. 发明申请

WO2019057572A1 HANDLING DETECTOR PIXEL PERFORMANCE VARIATION IN DIGITAL POSITRON EMISSION TOMOGRAPHY 审中-公开
公开(公告)号：WO2019057572A1
公开(公告)日：2019-03-28
申请号：PCT/EP2018/074546
申请日：2018-09-12
申请人： KONINKLIJKE PHILIPS N.V.
发明人： BAI, Chuanyong , ANDREYEV, Andriy , LIN, Sushen , ZHANG, Bin , MILLER, Michael, Allen , SONG, Xiyun , YE, Jinghan , DWIVEDI, Shekhar , HU, Zhiqiang , HSIEH, Yu-Lung , BRODSKIY, Ilya , BULGRIN, Thomas, Christopher , ZHU, Yang-Ming , MCKNIGHT, Douglas, B
IPC分类号： G01T1/29
摘要： A non-transitory computer-readable medium storing instructions readable and executable by a workstation (18) including at least one electronic processor (20) to perform a quality control (QC) method (100). The method includes: receiving a current QC data set acquired by a pixelated detector (14) and one or more prior QC data sets acquired by the pixelated detector; determining stability levels of detector pixels (16) of the pixelated detector over time from the current QC data set and the one or more prior QC data sets; labeling a detector pixel of the pixelated detector as dead when the stability level determined for the detector pixel is outside of a stability threshold range; and displaying, on a display device (24) operatively connected with the workstation, an identification (28) of the detector pixels labelled as dead.

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