Improving diffuse optical tomography imaging with adaptive regularization method

Haijing Niu; Ping Guo; Lijun Ji; Tianzi Jiang

doi:10.1117/12.751641

14 November 2007 Improving diffuse optical tomography imaging with adaptive regularization method

Haijing Niu, Ping Guo, Lijun Ji, Tianzi Jiang

Proceedings Volume 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques; 67891K (2007) https://doi.org/10.1117/12.751641
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

Diffuse optical tomography (DOT) is to reconstruct the images of internal optical parameters distribution from boundary measurements. Due to the amount of available boundary measurements is less than the number of unknown optical parameters to be recovered, this inverse problem usually shows the ill-posed characteristics. This will result in the problem of low reconstruction image quality. In this paper, an adaptive regularization method based on the objective function values is proposed, which reduces the ill-posed characteristics in the inverse problem by selecting an appropriate regularization value at teach iteration. Results from computer simulations indicated that using this regularization technique, DOT imaging quality is improved effectively. Furthermore, using the regularization technique, the sensitivity to noise of the reconstructed images can be decreased greatly.

Citation Download Citation

Haijing Niu, Ping Guo, Lijun Ji, and Tianzi Jiang "Improving diffuse optical tomography imaging with adaptive regularization method", Proc. SPIE 6789, MIPPR 2007: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 67891K (14 November 2007); https://doi.org/10.1117/12.751641

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