Fluorescence molecular tomography of permissible region selected by ISODATA

Yu-qing HOU; Yue-lin HU; Huang-jian YI; Pu JIAO; Xiao-wei HE

doi:10.3788/OPE.20182608.2074

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Fluorescence molecular tomography of permissible region selected by ISODATA

Information Sciences | 更新时间：2020-08-13

- Fluorescence molecular tomography of permissible region selected by ISODATA
- Optics and Precision Engineering Vol. 26, Issue 8, Pages: 2074-2083(2018)
- 作者机构：
  
  西北大学信息科学与技术学院西安市影像组学与智肾感知重点实验室, 陕西西安 710127
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20182608.2074
  CLC： TP391;Q632
- Received：16 November 2017，
  
  Accepted：16 January 2018，
  
  Published：25 August 2018
- 稿件说明：
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Yu-qing HOU, Yue-lin HU, Huang-jian YI, et al. Fluorescence molecular tomography of permissible region selected by ISODATA[J]. Optics and precision engineering, 2018, 26(8): 2074-2083.
DOI：

Yu-qing HOU, Yue-lin HU, Huang-jian YI, et al. Fluorescence molecular tomography of permissible region selected by ISODATA[J]. Optics and precision engineering, 2018, 26(8): 2074-2083. DOI： 10.3788/OPE.20182608.2074.

摘要

为了实现快速、准确、鲁棒的荧光分子断层成像（FMT）重建，有限投影FMT和可行域选取策略得到了越来越多的关注。为了解决现有的可行域选取方法中存在的参数设置困难以及多目标选取不准确的问题，从而提高有限投影FMT的重建质量，提出了应用迭代自组织数据分析技术算法（ISODATA）的FMT可行域选取方法。首先采用ISODATA对初级重建结果聚类分区，然后在各分离的区域上分别选取可行域。为了验证提出的方法在应用中的可行性和有效性，设计了三目标荧光团重建的对比实验。实验结果显示，使用2个投影数据时，只有使用本文提出的方法可以准确地重建出三个荧光源的位置；使用4个投影数据时，重建的平均位置误差为0.18 mm，荧光产额相对误差小于50%，而此时使用阈值法不能重建，使用区域收缩法的荧光产额相对误差为61.2%。即使在测量数据较少时，提出的方法也可以准确高效地选取可行域，提高有限投影FMT重建的精确度和鲁棒性。

Abstract

In order to achieve a fast

accurate

and robust reconstruction of fluorescence molecular tomography (FMT)

limited-projection FMT and permissible region selection methods have been drawing more and more attention. Aiming to solve the problems of existing permissible region selection methods including the difficulty of parameter setting and the inaccuracy of multi-objective selection

so as to improve reconstruction quality of the limited-projection FMT

a method through which permissible regions were selected by applying an iterative self-organizing data analysis technique algorithm (ISODATA) was proposed. Firstly

ISODATA was used to cluster the primary reconstruction results

and then permissible regions were selected at every separated cluster. A contrast experiment of reconstructing three target fluorophores was designed to verify the feasibility and effectiveness in the application. The experimental results indicate that positions of all the three fluorophores can be reconstructed accurately with two projections only by using the proposed selection method. With four projections

the average localization error of reconstruction results is 0.18 mm and the relative error of the fluorescence yield is less than 50%. Meanwhile

the threshold method fails to reconstruct and the relative error of the fluorescence yield using the region-shrinking method is 61.2%. The proposed method is able to select permissible regions accurately and efficiently even with little measurement data. Consequently

the accuracy and robustness of limited-projection FMT reconstruction are improved.

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Keywords

references

DAML G M, THEMELIS G, CRANEL L M, et al.. Intraoperative tumor-specific fluorescence imaging in ovarian cancer by folate receptor-α targeting:first in-human results[J]. Nature Medicine, 2011, 17(10):1315-1319.

DELIOLANIS N C, NTZIACHRISTOS V. Fluorescence molecular tomography of brain tumors in mice[J]. Cold Spring Harbor Protocols, 2013, 2013(5):438-443.

GAEDICKE S, BRAUN F, PRASAD S, et al.. Noninvasive positron emission tomography and fluorescence imaging of CD133+ tumor stem cells[J]. Proceedings of the National Academy of Sciences of the United States of America, 2014, 111(6):E692-E701.

CAO X, ZHANG B, LIU F, et al.. Reconstruction for limited-projection fluorescence molecular tomography based on projected restarted conjugate gradient normal residual[J]. Optics Letters, 2011, 36(23):4515-4517.

HE Y, CAO X, LIU F, et al.. Influence of limited-projection on fluorescence molecular tomography[J]. Journal of Innovative Optical Health Sciences, 2012, 05(03):460-466.

SHI J, LIU F, ZHANG J, et al.. Fluorescence molecular tomography reconstruction via discrete cosine transform-based regularization[J]. Journal of Biomedical Optics, 2015, 20(5):055004.

YI H J, ZHANG X, PENG J Y, et al.. Reconstruction for limited-projection fluorescence molecular tomography based on a double-mesh strategy[J]. BioMed Research International, 2016, 2016:5682851.

LIU X, YAN ZH ZH, LU H B. Performance evaluation of a priori information on reconstruction of fluorescence molecular tomography[J]. IEEE Access, 2015, 3:64-72.

CHEN D F, LIANG J M, LI Y, et al.. A sparsity-constrained preconditioned Kaczmarz reconstruction method for fluorescence molecular tomography[J]. BioMed Research International, 2016, 2016, 4504161.

ZHANG J L, SHI J W, CAO X, et al.. Fast reconstruction of fluorescence molecular tomography via a permissible region extraction strategy[J]. Optical Society of America A, 2014, 31(8):1886-1894.

FENG J CH, JIA K B, YAN G R, et al.. An optimal permissible source region strategy for multispectral bioluminescence tomography[J]. Optics Express, 2008, 16(20):15640-15654.

NASER M A, PATTERSON M S. Improved bioluminescence and fluorescence reconstruction algorithms using diffuse optical tomography, normalized data, and optimized selection of the permissible source region[J]. Biomedical Optics Express, 2011, 2(1):169-184.

HE X W, DONG F, YU J J, et al.. Reconstruction algorithm for fluorescence molecular tomography using sorted L-one penalized estimation[J]. Optical Society of America A, 2015, 32(11):1928-1935.

侯榆青, 曲璇, 张海波, 等.采用快速贝叶斯匹配追踪的单视图X射线发光断层成像[J].光学精密工程, 2017, 25(5):1159-1170.

HOU Y Q, QU X, ZHANG H B, et al.. Single-view XLCT imaging based on fast Bayesian matching pursuit[J]. Opt. Precision Eng., 2017, 25(5):1159-1170. (in Chinese)

RIPOLL J, SCHULZ R B, NTZIACHRISTOS V. Free-space propagation of diffuse light:theory and experiments[J]. Physical Review Letters, 2003, 91(10):103901.

CONG A X, WANG G. A finite-element-based reconstruction method for 3D fluorescence tomography[J]. Optics Express, 2005, 13(24):9847-9857.

BALL G H, HALL D J. ISODATA, a novel method of data analysis and pattern classification[R]. California: Stanford Research Institute, 1965.

MEMARSADEGHI N, MOUNT D M, NETANYAHU N S, et al.. A fast implementation of the ISODATA clustering algorithm[J]. International Journal of Computational Geometry and Applications, 2007, 17(1):71-103.

YI H J, CHEN D F, QU X CH, et al.. Multilevel, hybrid regularization method for reconstruction of fluorescent molecular tomography[J]. Applied Optics, 2012, 51(7):975-986.

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