Prior image constrained compressed sensing (PICCS)

Guang-Hong Chen; Jie Tang; Shuai Leng

doi:10.1117/12.770532

3 March 2008 Prior image constrained compressed sensing (PICCS)

Guang-Hong Chen, Jie Tang, Shuai Leng

Proceedings Volume 6856, Photons Plus Ultrasound: Imaging and Sensing 2008: The Ninth Conference on Biomedical Thermoacoustics, Optoacoustics, and Acousto-optics; 685618 (2008) https://doi.org/10.1117/12.770532
Event: SPIE BiOS, 2008, San Jose, California, United States

Abstract

It has been known for a long time that, in order to reconstruct a streak-free image in tomography, the sampling of view angles should satisfy the Shannon/Nyquist criterion. When the number of view angles is less than the Shannon/Nyquist limit, view aliasing artifacts appear in the reconstructed images. Most recently, it was demonstrated that it is possible to accurately reconstruct a sparse image using highly undersampled projections provided that the samples are distributed at random. The image reconstruction is carried out via an l₁ norm minimization procedure. This new method is generally referred to as compressed sensing (CS) in literature. Specifically, for an N×N image with significant image pixels, the number of samples for an accurate reconstruction of the image is . In medical imaging, some prior images may be reconstructed from a different scan or from the same acquired time-resolved data set. In this case, a new image reconstruction method, Prior Image Constrained Compressed Sensing (PICCS), has been recently developed to reconstruct images using a vastly undersampled data set. In this paper, we introduce the PICCS algorithm and demonstrate how to use this new algorithm to solve problems in medical imaging.

Citation Download Citation

Guang-Hong Chen, Jie Tang, and Shuai Leng "Prior image constrained compressed sensing (PICCS)", Proc. SPIE 6856, Photons Plus Ultrasound: Imaging and Sensing 2008: The Ninth Conference on Biomedical Thermoacoustics, Optoacoustics, and Acousto-optics, 685618 (3 March 2008); https://doi.org/10.1117/12.770532

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