Sparse Recovery Methods Hold Promise for Diffuse Optical Tomographic Image Reconstruction

作者：Prakash Jaya^*; Shaw Calvin B; Manjappa Rakesh; Kanhirodan Rajan; Yalavarthy Phaneendra K

来源：IEEE Journal of Selected Topics in Quantum Electronics, 2014, 20(2): 6800609.

DOI：10.1109/JSTQE.2013.2278218

• Near infrared imaging
• diffuse optical tomography
• image reconstruction
• sparse recovery methods

The sparse recovery methods utilize the l(p)-normbased regularization in the estimation problem with 0 %26lt;= p %26lt;= 1. These methods have a better utility when the number of independent measurements are limited in nature, which is a typical case for diffuse optical tomographic image reconstruction problem. These sparse recovery methods, along with an approximation to utilize the l(0)-norm, have been deployed for the reconstruction of diffuse optical images. Their performancewas compared systematically using both numerical and gelatin phantom cases to show that these methods hold promise in improving the reconstructed image quality.

• 出版日期2014-4