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    • 3. 发明申请
    • INTERLEAVED BLACK AND BRIGHT BLOOD DYNAMIC CONTRAST ENHANCED (DCE) MRI
    • 交互式BLACK和BRIGHT BLOOD动态对比增强(DCE)MRI
    • WO2012143824A1
    • 2012-10-26
    • PCT/IB2012/051779
    • 2012-04-12
    • KONINKLIJKE PHILIPS ELECTRONICS N.V.PHILIPS INTELLECTUAL PROPERTY & STANDARDS GMBHUNIVERSITY OF WASHINGTONWANG, JinnanCHEN, HuijunBÖRNERT, PeterYUAN, Chun
    • WANG, JinnanCHEN, HuijunBÖRNERT, PeterYUAN, Chun
    • G01R33/563
    • G01R33/48G01R33/56316G01R33/5635
    • Interleaved black/bright imaging (IBBI) is performed using a magnetic resonance (MR) scanner (10) wherein the black blood module (52) of the IBBI includes: applying a first flow sensitization gradient; applying a spoiler gradient after applying the first flow sensitization gradient; applying a second flow sensitization gradient after applying the spoiler gradient wherein the second flow sensitization gradient has area equal to the first flow sensitation gradient but of opposite polarity; applying a slice selective radio frequency excitation pulse after applying the spoiler gradient; and performing a MR readout after applying the second flow sensitization gradient and after applying the slice selective radio frequency excitation wherein the readout acquires MR imaging data having blood signal suppression in the region excited by the slice selective radio frequency excitation pulse. The MR imaging data having blood signal suppression is reconstructed to generate black blood images (20), and MR imaging data generated by bright blood modules (50) of the IBBI is reconstructed to generate bright blood images (22).
    • 使用磁共振(MR)扫描器(10)进行交错黑/亮成像(IBBI),其中IBBI的黑血模块(52)包括:施加第一流感敏化梯度; 在应用第一流感敏化梯度后应用扰流板梯度; 在施加扰流板梯度之后施加第二流动增感梯度,其中第二流动增感梯度具有等于第一流动感觉梯度但具有相反极性的面积; 应用扰流板梯度后应用切片选择性射频激励脉冲; 以及在应用所述第二流敏增强梯度之后并且在施加所述切片选择性射频激发之后执行MR读出,其中所述读出器获取在由所述切片选择性射频激励脉冲激发的区域中具有血液信号抑制的MR成像数据。 重建具有血液信号抑制的MR成像数据以产生黑血图像(20),并重建由IBBI的亮血模块(50)产生的MR成像数据,以产生亮血图像(22)。
    • 6. 发明申请
    • DUAL SPACE DICTIONARY LEARNING FOR MAGNETIC RESONANCE (MR) IMAGE RECONSTRUCTION
    • 用于磁共振(MR)图像重建的双空间词典学习
    • WO2015164825A1
    • 2015-10-29
    • PCT/US2015/027648
    • 2015-04-24
    • YUAN, ChunZHOU, ZechenWANG, JinnanBALU, Niranjan
    • YUAN, ChunZHOU, ZechenWANG, JinnanBALU, Niranjan
    • G01R33/54
    • G01R33/5608G01R33/5611
    • This disclosure relates to techniques for magnetic resonance (MR) image reconstruction. A herein-described k-space dictionary learning (KDL) technique and a herein-described dual space dictionary learning (DSDL) technique can use dictionaries to approximate an image and/or a data matrix in a signal observation domain for MR imaging by a weighted sum of dictionary entries. A herein-described self-supporting tailored k-space estimation for parallel imaging (STEP) technique can use k-space partitioning and basis selection tailored procedures to promote a spatially variant signal subspace and incorporation into a self-supporting structured low rank model that enforces locality, sparsity, and rank deficiency properties. The model can be formulated into a constrained optimization problem solvable by an iterative algorithm.
    • 本公开涉及用于磁共振(MR)图像重建的技术。 本文所述的k空间字典学习(KDL)技术和本文所述的双空间字典学习(DSDL)技术可以使用字典来通过加权的(k)空间词典学习(DSDL)技术在MR成像的信号观察域中近似图像和/或数据矩阵 字典条目的总和。 本文描述的用于并行成像(STEP)技术的自支撑定制的k空间估计可以使用k空间划分和基本选择定制程序来促进空间变异的信号子空间并且并入到自我支持的结构化低阶模型中, 地方,稀疏性和等级缺陷属性。 该模型可以被形成一个由迭代算法解决的约束优化问题。