Iterative tomographic image reconstruction by Compressive Sampling

Adnan Hanif, Atif Bin Mansoor, Tahira Ejaz

Research output: Chapter in Book/Conference paperConference paper

2 Citations (Scopus)


Positron Emission Tomography (PET) and Single Photon Emission Computerized Tomography (SPECT) are essential medical imaging tools with inherent drawback of slow data acquisition process. With the knowledge that radionuclide images are sparse in transform domain, we have applied a novel concept of Compressive Sampling on them. The proposed approach aims to reconstruct images from fewer measurements, significantly reducing scan time and radio-pharmaceutical doze, with benefits for patients and health care economics. The reconstruction of tomographic images is realized by compressed sensing the 2-D Fourier projections. These 2-D projections being sparse in transform domain are sensed with fewer samples in k-space and are reconstructed without loss of fidelity. These undersampled Fourier projections can then be backprojected by employing the iterative reconstruction approach for a complete 3-D volume. Our work focuses on the acquisition of 2-D SPECT/PET projections based on compressive sampling and their reconstruction using a non-linear recovery algorithm. Compressive sampling of a phantom image and PET bone scan scintigraph with radial Fourier samples are performed. The reconstructions of these images are compared to conventionally sampled images with MSE, PSNR and a new image quality measure, Structure SIMilarity (SSIM). The results show high quality image reconstruction using considerably few measurements.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Number of pages4
Publication statusPublished - 1 Dec 2010
Externally publishedYes
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: 26 Sep 201029 Sep 2010


Conference2010 17th IEEE International Conference on Image Processing, ICIP 2010
CountryHong Kong
CityHong Kong

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