Title :
PET Image Reconstruction Using Mumford-Shah Regularization Coupled with L1Data Fitting
Author :
Zhou, Jian ; Shu, Huazhong ; Xia, Ting ; Luo, Limin
Author_Institution :
Dept. of Biol. Sci. & Med. Eng., Southeast Univ., Nanjing
Abstract :
In positron emission tomography (PET) image reconstruction, regularization methods are usually considered to suppress noise effects in reconstructed images. In this paper, we model this reconstruction problem in a new variational framework where the Mumford-Shah (MS) regularization coupled with recently developed L1 data fidelity term is adapted. In order to simplify the numerical computation, Ambrosio and Tortorelli\´s Gamma-convergence approximation is also employed to substitute the irregular parts (edge set) of MS functionals with the auxiliary smooth function. In numerical studies we compare our method with the "conventional" penalized least-square (PLS) algorithm with local nonquadratic Huber penalty. Results show both the feasibility and efficiency of the proposed algorithm
Keywords :
convergence; image reconstruction; least squares approximations; medical image processing; positron emission tomography; Gamma-convergence approximation; L1data fitting; Mumford-Shah regularization; PET; auxiliary smooth function; image reconstruction; local nonquadratic Huber penalty; penalized least-square algorithm; positron emission tomography; Active contours; Biomedical engineering; Biomedical imaging; Data engineering; Engineering in medicine and biology; Image reconstruction; Image segmentation; Inverse problems; Positron emission tomography; Robustness; Г-convergence; L; Mumford-Shah regularization; image reconstruction; penalized least-square; positron emission tomography;
Conference_Titel :
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location :
Shanghai
Print_ISBN :
0-7803-8741-4
DOI :
10.1109/IEMBS.2005.1616823
