Super-resolution x-ray luminescence optical tomography imaging

被引:0
|
作者
Tang, Xueli [1 ]
Han, Changpeng [2 ]
Liu, Xin [1 ]
机构
[1] Shanghai Univ, Sch Commun & Informat Engn, Shanghai 200444, Peoples R China
[2] Shanghai Univ TCM, Yueyang Hosp, Dept Coloproctol, Shanghai 200437, Peoples R China
基金
中国国家自然科学基金;
关键词
X-ray luminescence optical tomography; super-resolution imaging technique; image reconstruction; optical tomography; NANOPARTICLES; FLUORESCENCE; MICROSCOPY; MODEL;
D O I
10.1117/12.2537540
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
X-ray luminescence optical tomography (XLOT) is a promising in vivo noninvasive imaging technique. By using x-rays to irradiate nanophosphors (NPs) in imaged region, XLOT can achieve better imaging depth and higher imaging sensitivity than the widely used optical molecular tomographic imaging techniques, e.g., bioluminescence tomography (BLT) or fluorescence molecular tomography (FMT). However, compared with the anatomical imaging techniques, e.g., x-ray computed tomography (XCT), XLOT has the disadvantage of low spatial resolution limited to millimeters. To overcome the limitation, recently, many efforts have been dedicated to optimize the data acquisition schemes and improve reconstruction methods. Nevertheless, challenges remain in XLOT due to the light scattering in biological tissues and the severely ill-condition and ill-posed of the inverse problem of XLOT. To improve the spatial resolution of XLOT, inspired by super-resolution localization optical microscopy, in this work, we propose a novel imaging method, termed as SR-XLOT, which is achieved by locating the position of NPs in each frame by using the single emitter localization methods (e.g., Gaussian fitting method). After reconstructing the positions of NPs in each frame, a super-resolution XLOT image can be generated by superimposing the identified positions of NPs from all frames into one image. To evaluate the performance of the proposed SR-XLOT method, a series of numerical simulation experiments were performed. The experimental results indicate that when using SR-XLOT method, the spatial resolution of XLOT can be significantly improved, compared with the conventional reconstruction methods. As a result, the method makes it possible to implement a super-resolution XLOT imaging, which is attractive for medical diagnostic and drug research.
引用
收藏
页数:7
相关论文
共 50 条
  • [21] Super-resolution X-ray imaging with hybrid pixel detectors using electromagnetic source stepping
    Dreier, T.
    Lundstrom, U.
    Bech, M.
    JOURNAL OF INSTRUMENTATION, 2020, 15 (03)
  • [22] High-resolution x-ray luminescence computed tomography
    Lun, Michael C.
    Li, Changqing
    MEDICAL IMAGING 2020: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING, 2021, 11317
  • [23] Numerical simulation of x-ray luminescence optical tomography for small-animal imaging
    Li, Changqing
    Martinez-Davalos, Arnulfo
    Cherry, Simon R.
    JOURNAL OF BIOMEDICAL OPTICS, 2014, 19 (04)
  • [24] Method for improving the spatial resolution of narrow x-ray beam-based x-ray luminescence computed tomography imaging
    Zhang, Yueming
    Lun, Michael C.
    Li, Changqing
    Zhou, Zhongxing
    JOURNAL OF BIOMEDICAL OPTICS, 2019, 24 (08)
  • [25] Numerical and Experimental Studies of X-ray Luminescence Optical Tomography for Small Animal Imaging
    Li, Changqing
    Martinez Davalos, Arnulfo
    Cherry, Simon R.
    OPTICAL TOMOGRAPHY AND SPECTROSCOPY OF TISSUE X, 2013, 8578
  • [26] A balanced super-resolution optical fluctuation imaging method for super-resolution ultrasound
    Lv, Minglei
    Shu, Yuexia
    Liu, Ying
    Yan, Zhuangzhi
    Jiang, Jiehui
    Liu, Xin
    MEDICAL IMAGING 2018: BIOMEDICAL APPLICATIONS IN MOLECULAR, STRUCTURAL, AND FUNCTIONAL IMAGING, 2018, 10578
  • [27] Super-resolution computed tomography imaging spectrometry
    LEI YUAN
    QIANG SONG
    HECONG LIU
    KEVIN HEGGARTY
    WEIWEI CAI
    Photonics Research, 2023, 11 (02) : 212 - 224
  • [28] Super-resolution computed tomography imaging spectrometry
    Yuan, Lei
    Ong, Qiang
    Liu, Hecong
    Heggraty, Kevin
    Cai, Weiwei
    PHOTONICS RESEARCH, 2023, 11 (02) : 212 - 224
  • [29] Non-linear super-resolution computed tomography imaging algorithm based on a discrete X-ray source focal spot model
    Yang, Ping
    Shi, Ligen
    Duan, Jigang
    Sun, Qixiang
    Zhao, Xing
    OPTICS EXPRESS, 2024, 32 (25): : 44452 - 44477
  • [30] X-RAY FLUORESCENCE IMAGE SUPER-RESOLUTION USING DICTIONARY LEARNING
    Dai, Qiqin
    Pouyet, Emeline
    Cossairt, Oliver
    Walton, Marc
    Casadio, Francesca
    Katsaggelos, Aggelos
    2016 IEEE 12TH IMAGE, VIDEO, AND MULTIDIMENSIONAL SIGNAL PROCESSING WORKSHOP (IVMSP), 2016,