基于扩展卡尔曼滤波-长短期记忆神经网络校正模型的漫反射荧光断层成像性能增强技术

IF 2.9 2区 医学 Q2 BIOCHEMICAL RESEARCH METHODS
Lingxiu Xing, Limin Zhang, Wenjing Sun, Zhuanxia He, Yanqi Zhang, and Feng Gao
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引用次数: 0

摘要

为了缓解弥散荧光断层成像(DFT)重建的假定性,提高成像质量和速度,本文提出了一种模型衍生的深度学习方法,将扩展卡尔曼滤波(EKF)与长短期记忆(LSTM)神经网络相结合,将半迭代EKF(SEKF)获得的迭代过程参数作为LSTM神经网络校正模型的输入,用于预测最佳荧光分布。为了验证 SEKF-LSTM 算法的有效性,研究人员进行了一系列数值模拟、幻影和活体实验,并对实验结果进行了定量评估,并与传统的 EKF 算法进行了比较。模拟实验结果表明,所提出的新算法能有效提高重建图像的质量和重建速度。重要的是,由仿真数据训练的 LSTM 修正模型在实验数据中也获得了令人满意的结果,表明 SEKF-LSTM 算法具有很强的泛化能力和巨大的实际应用潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance enhancement of diffuse fluorescence tomography based on an extended Kalman filtering-long short term memory neural network correction model
To alleviate the ill-posedness of diffuse fluorescence tomography (DFT) reconstruction and improve imaging quality and speed, a model-derived deep-learning method is proposed by combining extended Kalman filtering (EKF) with a long short term memory (LSTM) neural network, where the iterative process parameters acquired by implementing semi-iteration EKF (SEKF) served as inputs to the LSTM neural network correction model for predicting the optimal fluorescence distributions. To verify the effectiveness of the SEKF-LSTM algorithm, a series of numerical simulations, phantom and in vivo experiments are conducted, and the experimental results are quantitatively evaluated and compared with the traditional EKF algorithm. The simulation experimental results show that the proposed new algorithm can effectively improve the reconstructed image quality and reconstruction speed. Importantly, the LSTM correction model trained by the simulation data also obtains satisfactory results in the experimental data, suggesting that the SEKF-LSTM algorithm possesses strong generalization ability and great potential for practical applications.
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来源期刊
Biomedical optics express
Biomedical optics express BIOCHEMICAL RESEARCH METHODS-OPTICS
CiteScore
6.80
自引率
11.80%
发文量
633
审稿时长
1 months
期刊介绍: The journal''s scope encompasses fundamental research, technology development, biomedical studies and clinical applications. BOEx focuses on the leading edge topics in the field, including: Tissue optics and spectroscopy Novel microscopies Optical coherence tomography Diffuse and fluorescence tomography Photoacoustic and multimodal imaging Molecular imaging and therapies Nanophotonic biosensing Optical biophysics/photobiology Microfluidic optical devices Vision research.
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