A fast reconstruction algorithm for bioluminescence tomography based on smoothed l0 norm regularization

Xiaowei He; Jingjing Yu; Guohua Geng; Hongbo Guo

doi:10.1117/12.2031509

27 October 2013 A fast reconstruction algorithm for bioluminescence tomography based on smoothed l₀ norm regularization

Xiaowei He, Jingjing Yu, Guohua Geng, Hongbo Guo

Proceedings Volume 8920, MIPPR 2013: Parallel Processing of Images and Optimization and Medical Imaging Processing; 89200Q (2013) https://doi.org/10.1117/12.2031509
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China

Abstract

As an important optical molecular imaging technique, bioluminescence tomography (BLT) offers an inexpensive and sensitive means for non-invasively imaging a variety of physiological and pathological activities at cellular and molecular levels in living small animals. The key problem of BLT is to recover the distribution of the internal bioluminescence sources from limited measurements on the surface. Considering the sparsity of the light source distribution, we directly formulate the inverse problem of BLT into an l₀-norm minimization model and present a smoothed l₀-norm (SL0) based reconstruction algorithm. By approximating the discontinuous l0 norm with a suitable continuous function, the SL0 norm method solves the problem of intractable computational load of the minimal l₀ search as well as high sensitivity of l₀-norm to noise. Numerical experiments on a mouse atlas demonstrate that the proposed SL0 norm based reconstruction method can obtain whole domain reconstruction without any a priori knowledge of the source permissible region, yielding almost the same reconstruction results to those of l₁ norm methods.

Citation Download Citation

Xiaowei He, Jingjing Yu, Guohua Geng, and Hongbo Guo "A fast reconstruction algorithm for bioluminescence tomography based on smoothed l₀ norm regularization", Proc. SPIE 8920, MIPPR 2013: Parallel Processing of Images and Optimization and Medical Imaging Processing, 89200Q (27 October 2013); https://doi.org/10.1117/12.2031509

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