Patents Assigned to Siemens Healthineers Ltd.
  • Publication number: 20230038549
    Abstract: In a method for measuring brain free water content, in response to an RF excitation field generated on the basis of a magnetic resonance fingerprinting sequence and applied to the brain, an equilibrium magnetization mixed term (M0) signal is acquired from radiation emitted by each excited voxel of the brain, to obtain an M0 value of each voxel of the brain; a receive coil sensitivity (RP) value of each voxel of the brain is acquired; the M0 value of each voxel of the brain is divided by the RP value of the corresponding voxel to obtain a proton density (PD) value of each voxel of the brain; a PD value of cerebrospinal fluid is taken to be a reference PD value; and the PD value of each voxel of the brain is divided by the reference PD value to obtain the free water content of each voxel of the brain. The method advantageously increases the speed and accuracy of measurement of brain free water content.
    Type: Application
    Filed: July 29, 2022
    Publication date: February 9, 2023
    Applicants: Siemens Healthineers Ltd., Henan Provincial People's Hospital
    Inventors: Mei Yun Wang, Xian Chang Zhang, Yan Bai, Rui Zhang, Ru Shi Chen
  • Publication number: 20200337626
    Abstract: Techniques are disclosed for measuring the corpus callosum volume of a fetus using magnetic resonance imaging. A scanogram of a fetus is acquired, and a detection area is determined using the corpus callosum position of the fetus in the scanogram. Magnetic resonance scanning is performed on the detection area to obtain a diffusion weighted image, with a gradient direction that is orthogonal or normal to an extending direction of fiber bundles of the corpus callosum. A fetal head image is cropped in the diffusion weighted image, and a predetermined threshold is applied to obtain an image including pixels having a brightness value that is greater than the threshold. Image processing is performed on the binarized image, with the largest region therein being identified as the corpus callosum, and the sum of voxel dimensions associated with the signal of the largest region being calculated as the corpus callosum volume.
    Type: Application
    Filed: April 24, 2020
    Publication date: October 29, 2020
    Applicants: Siemens Healthineers Ltd., Shandong Medical Imaging Research Institute
    Inventors: Guangbin Wang, Tian Yi Qian, Xin Chen, Cong Sun
  • Publication number: 20200300949
    Abstract: The present disclosure related to techniques for implementing Chemical Exchange Saturation Transfer-Magnetic Resonance Imaging (CEST-MRI) sequence generation. The techniques include starting a CEST-MRI scanning process, and generating and transmitting a CEST pre-saturation pulse. When transmission of the CEST pre-saturation pulse has ended, the MRI device generates and transmits a fat-suppression pulse. When transmission of the fat-suppression pulse has ended, the MRI device generates and transmits an excitation pulse. When transmission of the excitation pulse has ended, the MRI device generates and transmits multiple non-slice-selective refocusing square-wave pulses. The present disclosure functions to increase the spatial coverage and MR signal acquisition speed of CEST-MRI imaging.
    Type: Application
    Filed: March 19, 2020
    Publication date: September 24, 2020
    Applicants: Siemens Healthineers Ltd., Zhejiang University
    Inventors: Yi Zhang, Dan Wu, Yi Sun
  • Publication number: 20200096592
    Abstract: A magnetic resonance diffusion tensor imaging method and corresponding device. The method includes acquiring omnidirectionally sampled diffusion weighted images of a plurality of training samples; performing diffusion tensor model fitting and undersampling for the omnidirectionally sampled diffusion weighted images of each training sample to obtain an omnidirectionally sampled diffusion tensor image and an undersampled diffusion weighted image; training a deep learning network, with the omnidirectionally sampled diffusion tensor images of the plurality of training samples as training targets and the undersampled diffusion weighted images as training data; acquiring undersampled diffusion weighted images of a target object; and inputting the undersampled diffusion weighted images of target objects into the trained deep learning network to obtain the predicted omnidirectionally sampled diffusion tensor images of the target objects. Also, a fiber tracking method and corresponding device.
    Type: Application
    Filed: September 25, 2019
    Publication date: March 26, 2020
    Applicant: Siemens Healthineers Ltd.
    Inventors: Jianhui Zhong, Mu Lin, Yi Sun