Simulation of 4D spectral-spatial EPR images

被引:23
|
作者
Ahn, Kang-Hyun
Halpern, Howard J. [1 ]
机构
[1] Univ Chicago, Dept Radiat & Cellular Oncol, Chicago, IL 60637 USA
[2] Univ Chicago, Ctr EPR Imaging Vivo Physiol, Chicago, IL 60637 USA
关键词
EPR; 4D EPRI; tomography; spectral-spatial imaging; simulation;
D O I
10.1016/j.jmr.2007.02.013
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Electron paramagnetic resonance imaging (EPRI) can be modeled by the forward projection of a 4D synthetic spectral- spatial phantom. We developed a simulation tool for EPRI and carried out a quantitative comparison between simulation and experiment, focusing on the signal and noise characteristics. The signal height in the simulation was compared to that in the experimental projections at gradients of different magnitudes and directions. We investigated the noise power spectrum of an EPR imager and incorporated it into the simulation. The signal and noise modeling of the simulation achieved the same performance as the EPR imager. Using this simulation, various sampling schemes were tried to find an optimized parameter set under the customized noise model of this EPR imager. (c) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码:1 / 9
页数:9
相关论文
共 50 条
  • [41] Spectral-Spatial Sparse Subspace Clustering for Hyperspectral Remote Sensing Images
    Zhang, Hongyan
    Zhai, Han
    Zhang, Liangpei
    Li, Pingxiang
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2016, 54 (06): : 3672 - 3684
  • [42] Determination of Spectral-Spatial Resolution of Hyperspectral Images For Retinal Imaging Applications
    Baba, Justin S.
    Kashani, Amir H.
    Karnowski, Thomas Paul
    Martin, Gabriel
    Humayun, Mark S.
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2014, 55 (13)
  • [43] Pansharpening Based on Spectral-Spatial Dependence for Multibands Remote Sensing Images
    Wu, Lei
    Jiang, Xunyan
    IEEE ACCESS, 2022, 10 : 76153 - 76167
  • [44] Multi-scale superpixel spectral-spatial classification of hyperspectral images
    Li, Shanshan
    Ni, Li
    Jia, Xiuping
    Gao, Lianru
    Zhang, Bing
    Peng, Man
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2016, 37 (20) : 4905 - 4922
  • [45] Locality Adaptive Discriminant Analysis for Spectral-Spatial Classification of Hyperspectral Images
    Wang, Qi
    Meng, Zhaotie
    Li, Xuelong
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2017, 14 (11) : 2077 - 2081
  • [46] An Improved Spectral-Spatial Classification Framework for Hyperspectral Remote Sensing Images
    Chen, Zhao
    Wang, Bin
    2014 INTERNATIONAL CONFERENCE ON AUDIO, LANGUAGE AND IMAGE PROCESSING (ICALIP), VOLS 1-2, 2014, : 532 - 536
  • [47] Restoring the spatial resolution of refocus images on 4D light field
    Lim, JaeGuyn
    Park, ByungKwan
    Kang, JooYoung
    Lee, SeongDeok
    COMPUTATIONAL IMAGING VIII, 2010, 7533
  • [48] Comparison of local and global angular interpolation applied to spectral-spatial EPR image reconstruction
    Ahn, Kang-Hyun
    Halpern, Howard J.
    MEDICAL PHYSICS, 2007, 34 (03) : 1047 - 1052
  • [49] Deep Multiscale Spectral-Spatial Feature Fusion for Hyperspectral Images Classification
    Liang, Miaomiao
    Jiao, Licheng
    Yang, Shuyuan
    Liu, Fang
    Hou, Biao
    Chen, Huan
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2018, 11 (08) : 2911 - 2924
  • [50] Spectral-spatial classification of hyperspectral images using deep Boltzmann machines
    Yang J.
    Wang X.
    Liu S.
    Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University, 2019, 46 (03): : 109 - 115