A NEW APPROACH TO IMPROVE OPTIMIZER PERFORMANCE THROUGH ALGORITHMS DIVERSIFICATION FOR IMAGE RECONSTRUCTION IN DIFFUSE OPTICAL TOMOGRAPHY

被引：0
|
作者：
Chakhim, Nada [1 ]
Louzar, Mohamed [1 ]
Alaoui, Mohammed [1 ]
机构：
[1] Univ Hassan First, Fac Sci & Technol, MISI Lab, Settat 26000, Morocco
来源：
COMMUNICATIONS IN MATHEMATICAL BIOLOGY AND NEUROSCIENCE | 2021年
关键词：
diffuse optical tomography; inverse problem; diversification; random switching algorithm; image reconstruction; statistical simulation; SPECTROSCOPY;
D O I：
10.28919/cmbn/6835
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this work, we explore a different way to construct optimizer algorithms for solving the inverse problem of Diffuse Optical Tomography by using diversification of two stochastic gradient-based algorithms, namely NADAM and AMSGrad. We will study the speed of convergence of the proposed new breed of algorithms, also we will discuss the quality of reconstructed images in both cases of free of noise and noisy measurement data. For analysis and exploration of the potential of the proposed algorithm, we use statistical simulations and analysis approach.
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页数：19
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