Inverse surfacelet transform for image reconstruction with constrained-conjugate gradient methods

W Huang, Y Wang, DW Rosen - … of computing and …, 2014 - asmedigitalcollection.asme.org
Image reconstruction is the transformation process from a reduced-order representation to
the original image pixel form. In materials characterization, it can be utilized as a method to …

Image renovation in positron emission tomography using recursive algorithm

T Arunprasath, MP Rajasekaran… - 2012 IEEE …, 2012 - ieeexplore.ieee.org
This paper explains the image reconstruction in Positron Emission Tomography using
Maximum a Posterior (MAP). Till date, Diagnostic reconstruction methods offer a direct …

Performance evaluation of PET image reconstruction using radial basis function networks

T Arunprasath, MP Rajasekaran, S Kannan… - Artificial Intelligence and …, 2015 - Springer
In this paper, for the reconstruction of the positron emission tomography (PET) images,
Artificial Neural Network (ANN) method and Artificial Neural Network-Radial Basis Function …

Neural network segmented CD algorithm–based PET liver image reconstruction

TA Prasath, MP Rajasekaran… - International Journal of …, 2015 - inderscienceonline.com
In this paper, reconstruction of the Positron Emission Tomography (PET) images, a CD
algorithm was instigated with NN based image segmentation techniques called Neural …

Analysis of fuzzy segmented based reconstructed pet liver image using mlem algorithm

T Arunprasath, S Saraswathy… - … IEEE Conference on …, 2013 - ieeexplore.ieee.org
This paper possess the fuzzy segmented based performance analysis for the reconstruction
of a non linear PET Liver image using fuzzy logic controlled Maximum Likelihood …

A Quantitative Assessment of PET Brain Image Reconstruction using MAP and Neural Network based Segmentation of CG Algorithm

T Arunprasath, MP Rajasekaran… - International Journal of …, 2014 - cspub-ijcisim.org
This paper addresses a comparative analysis of PET Brain image reconstruction based on
iterative and weighted least-square (WLS) algorithms. In previous years, the analytical …