Yoo, J., et al. (2020) Deep Learning Diffuse Optical Tomography. IEEE Transactions on Medical Imaging, 39, 877-887.
https://doi.org/10.1109/TMI.2019.2936522

has been cited by the following article:

• TITLE: Application of Reconstruction and Optimization Algorithms in Optical Tomography

  AUTHORS: Umair Sajjad Hashmi, Raheel Muzzammel, Rabia Arshad, Saba Mehmood

  KEYWORDS: Optical Tomography, Medical Imaging, Image Reconstruction, Optimization, Forward Problem, Inverse Problem

  JOURNAL NAME: World Journal of Engineering and Technology, Vol.8 No.2, April 20, 2020

  ABSTRACT: Optical tomography is a non-invasive technique that uses visible or near infrared radiation to analyze biological tissues. Researchers take immense attention towards advancement in optical tomography because of its low cost and an advantage of providing anatomical information. Based on the information of optical characteristics, forward and inverse problem of tomography are solved. In this research, finite element method is employed for forward problem and gradient-based optimization algorithm is developed for inverse problem of optical tomography. It is found from simulations that information about imaging is processed more distinctly and in less computational time. Normal and abnormal conditions in imaging are readily distinguished.Simulations are carried out in Matlab. Different scenarios are developed and are simulated to validate the performance of reconstruction and optimization algorithms in optical tomography.