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- W2380918008 abstract "Optical tomography reconstruction is an ill-posed problem and the errors in the measurement data will be amplified in the process of reconstruction.In order to solve the problem of ill-posedness,a new kind of reconstruction algorithm was proposed in this paper,in which the Generalized Gaussian Markov Random Field(GGMRF) was used to model the unknown image.The reconstruction process was an optimization process on objective function in essence,but the gradient computation of the objective function with respect to optical parameters was difficult.Therefore,a novel gradient computation strategy based on gradient tree was presented.In experiments,reconstructed results corresponding to the absorption coefficients and the scattering coefficients were given.In order to evaluate the quality of reconstructed images,three criteria were imported,and their values for images from different reconstruction algorithms were listed.Finally,the validity of the model-based reconstruction algorithm was analyzed by the comparison of reconstructed images and the values of three criteria." @default.
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- W2380918008 date "2007-01-01" @default.
- W2380918008 modified "2023-09-25" @default.
- W2380918008 title "Model-based image reconstruction algorithm for optical tomography" @default.
- W2380918008 hasPublicationYear "2007" @default.
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