Abstract
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 language | English |
|---|---|
| Title of host publication | 2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings |
| Pages | 4313-4316 |
| Number of pages | 4 |
| DOIs | |
| Publication status | Published - 1 Dec 2010 |
| Externally published | Yes |
| Event | 2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong Duration: 26 Sep 2010 → 29 Sep 2010 |
Conference
| Conference | 2010 17th IEEE International Conference on Image Processing, ICIP 2010 |
|---|---|
| Country | Hong Kong |
| City | Hong Kong |
| Period | 26/09/10 → 29/09/10 |
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Iterative tomographic image reconstruction by Compressive Sampling. / Hanif, Adnan; Mansoor, Atif Bin; Ejaz, Tahira.
2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings. 2010. p. 4313-4316 5652461.Research output: Chapter in Book/Conference paper › Conference paper
TY - GEN
T1 - Iterative tomographic image reconstruction by Compressive Sampling
AU - Hanif, Adnan
AU - Mansoor, Atif Bin
AU - Ejaz, Tahira
PY - 2010/12/1
Y1 - 2010/12/1
N2 - 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.
AB - 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.
KW - Compressive sampling
KW - Convex optimization
KW - Fourier projections
KW - Radionuclide imaging
UR - http://www.scopus.com/inward/record.url?scp=78651101429&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2010.5652461
DO - 10.1109/ICIP.2010.5652461
M3 - Conference paper
SN - 9781424479948
SP - 4313
EP - 4316
BT - 2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
ER -