Method for tissue classification, computer program product and magnetic resonance imaging system

    公开(公告)号:US10987020B2

    公开(公告)日:2021-04-27

    申请号:US15772149

    申请日:2016-10-17

    Abstract: It is an object of the invention to improve tissue classification in MRI images. In particular it is an object of the invention to improve the classification of bone and air in MRI images. This object is achieved by a method for tissue classification in a region of interest in a magnetic resonance (MR) image comprising a first region and a second region, wherein the first region represents air and the second region represents bone. The method comprises the steps of: —acquiring a first magnetic resonance image comprising the first and the second region and; —acquiring a second magnetic resonance image comprising the first and the second region, wherein the first region has a different shape in the second magnetic resonance image compared to the first magnetic resonance image and; —identifying the first region and second region in the first and second image and; —comparing the first image and the second image with respect to the first region and the second region and; —classifying the first region as region representing air based on a presence of a shape difference between the first and the second image and classifying the second region as bone based on an absence of the shape difference between the first and second image.

    Gradient impulse response function mapping

    公开(公告)号:US10830856B2

    公开(公告)日:2020-11-10

    申请号:US16340492

    申请日:2017-09-28

    Abstract: A magnetic resonance imaging system includes a gradient system and a processor for controlling the magnetic resonance imaging system. Execution of machine executable instructions causes the magnetic resonance imaging system to: acquire by coil elements first magnetic resonance data simultaneously from a group of passive local probes, wherein the first group of passive local probes includes a plurality of passive local probes located spaced apart from each other; disentangle contributions to the first magnetic resonance data from the individual local probes, calculate for the magnetic resonance imaging system a gradient impulse response function of the gradient system using the first magnetic resonance data from the local probes; and determine correction factors using the gradient impulse response function

    MR-based attenuation correction in PET/MR imaging with Dixon pulse sequence

    公开(公告)号:US10274562B2

    公开(公告)日:2019-04-30

    申请号:US14916297

    申请日:2014-09-18

    Abstract: A medical imaging system (10) includes a nuclear imaging system (62), a timing optimization unit (40), a magnetic resonance (MR) scanner (12), an MR reconstruction unit (38), and an attenuation map unit (50). The nuclear imaging system (62) receives nuclear decay data and generates at least one nuclear image (64) of a first resolution based on the received nuclear decay data of an imaged subject (16) and an attenuation map (52). The timing optimization unit (40) which selects a first and a second echo time for a modified Dixon (mDixon) pulse sequence and a sufficient number of repetition times (TRs) to generate an image of the subject (16) of at least a first resolution, with the phase angle difference between water and fat at the first and the second echo time being unequal to 0° and 180°. The MR scanner (12) applies the sequence to the subject (16) and receives MR data (32) from the subject. The MR reconstruction unit (38) reconstructs at least one MR image (44) based on the MR data (32). The attenuation map unit (50) constructs the attenuation map (52) based on the reconstructed MR image (44).

    Tumor segmentation and tissue classification in 3D multi-contrast
    15.
    发明授权
    Tumor segmentation and tissue classification in 3D multi-contrast 有权
    肿瘤分割和组织分类3D多重对比

    公开(公告)号:US09547061B2

    公开(公告)日:2017-01-17

    申请号:US14374652

    申请日:2013-01-25

    Abstract: A medical imaging system (5) includes a workstation (20), a coarse segmenter (30), a fine segmenter (32), and an enclosed tissue identification module (34). The workstation (20) includes at least one input device (22) for receiving a selected location as a seed in a first contrasted tissue type and a display device (26) which displays a diagnostic image delineating a first segmented region of a first tissue type and a second segmented region of a second contrasted tissue type and identified regions which include regions fully enclosed by the first segmented region as a third tissue type. The coarse segmenter (30) grows a coarse segmented region of coarse voxels for each contrasted tissue type from the seed location based on a first growing algorithm and a growing fraction for each contrasted tissue type. The seed location for growing the second contrasted tissue type includes the first coarse segmented region and any fully enclosed coarse voxels, and each coarse voxel includes an aggregation of voxels and a maximum and a minimum of the voxel intensities. The fine segmenter (32) grows a segmented region of voxels for each contrasted tissue type from the seed location and bounded by the second coarse segmented region based on a second growing algorithm and a growing fraction for each contrasted tissue type initially set to the growing fraction for the corresponding region. The seed location for growing the second contrasted tissue type includes the first segmented region and any identified regions. The enclosed tissue identification module (34) identifies any regions of voxels fully enclosed by the first segmented region as being of the third tissue type. The coarse segmenter, the fine segmenter, and the enclosed tissue identification module are implemented by an electronic data processing device.

    Abstract translation: 医疗成像系统(5)包括工作站(20),粗分割器(30),精细分割器(32)和封闭的组织识别模块(34)。 工作站(20)包括至少一个输入装置(22),用于以第一对比组织类型的种子的形式接收所选择的位置,以及显示装置(26),其显示描绘第一组织类型的第一分割区域 以及第二对比组织类型的第二分割区域和被识别的区域,其包括由第一分割区域完全包围的区域作为第三组织类型。 粗分割器(30)基于第一生长算法和每个对比组织类型的生长部分,从种子位置为每个对比组织类型生长粗体素的粗分割区域。 用于生长第二对比组织类型的种子位置包括第一粗分段区域和任何完全封闭的粗体素,并且每个粗体素包括体素的聚集和体素强度的最大和最小值。 细分割器(32)基于第二种生长算法,从种子位置生长每个对比组织类型的分形区域,并由第二粗分段区域生长,并且对于初始设置为生长部分的每个对比组织类型的生长部分 对于相应的区域。 用于生长第二对比组织类型的种子位置包括第一分割区域和任何识别的区域。 封闭的组织识别模块(34)将由第一分段区域完全包围的体素的任何区域识别为第三组织类型。 粗分割器,精细分割器和封闭组织识别模块由电子数据处理装置实现。

    MR RECEIVE COIL LOCALIZATION AND MR-BASED ATTENUATION CORRECTION
    16.
    发明申请
    MR RECEIVE COIL LOCALIZATION AND MR-BASED ATTENUATION CORRECTION 审中-公开
    接收线圈定位和基于MR的衰减校正

    公开(公告)号:US20150196222A1

    公开(公告)日:2015-07-16

    申请号:US14419751

    申请日:2013-08-09

    Abstract: A system (10) and method generate one or more MR data sets of an imaging volume (16) using an MR scanner (14). The imaging volume (16) includes one or more of a region of interest (ROI), the ROI including a metal element, and a local receive coil (18) of the MR scanner (14). At least one of an attenuation, confidence or density map accounting for the metal element is generated and the location of the local receive coil (18) within the imaging volume (16) is determined. The generating includes identification of the metal element within the ROI based on a phase map of the ROI generated from the MR data sets. The determining includes registering a known sensitivity profile of the local receive coil (18) to a sensitivity map of the local receive coil (18) generated from the MR data sets.

    Abstract translation: 系统(10)和方法使用MR扫描器(14)生成成像体积(16)的一个或多个MR数据集。 成像体积(16)包括感兴趣区域(ROI)中的一个或多个,ROI包括金属元件和MR扫描仪(14)的局部接收线圈(18)。 产生对金属元件的衰减,置信度或密度图中的至少一个,并且确定成像体积(16)内的局部接收线圈(18)的位置。 该生成包括基于从MR数据集生成的ROI的相位图来识别ROI内的金属元​​素。 确定包括将本地接收线圈(18)的已知灵敏度分布记录到从MR数据集生成的本地接收线圈(18)的灵敏度映射。

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