Dimensionality Reduced Plug and Play Priors for Improving Photoacoustic Tomographic Imaging with Limited Noisy Data

This MATLAB code was used as part of the work presented in

Navchetan Awasthi, Sandeep Kumar Kalva, Manojit Pramanik, Phaneendra K. Yalavarthy, “Dimensionality Reduced Plug and Play Priors for Improving Photoacoustic Tomographic Imaging with Limited Noisy Data,”(in Press)

**The raw measurement data for the experimental experiments is not provided and can be requested.

***Please contact if you find any mistakes or if you need any help regarding the codes.

Matlab Codes: (requires SALSA_v2.0)

#The codes for generating the data and TV can be found at patextrapolation site.

#Matlab implementation for generating result of all the numerical phantoms : Generating_All_phantom_data_Results.m

#Matlab implementation for comparing all the results for the phantom images : all_comparisons.m

#Matlab implementation for TV denoising : perform_tv_denoising.m

#Supplementary file for perform_tv_denoising : compute_total_variation.m

#Matlab Implementation of Lanczos Tikhonov Heuristic and BPD_LSQR methods:demo_bpd_lsqr_40.m

# Supplementary files required : bpd_lsqr.m , bpd_salsa_sparsemtx.m , lsqr_b_hybrid.m , pythag.m , soft.m