@article{oai:tsukuba.repo.nii.ac.jp:00038333,
 author = {工藤, 博幸 and Rashed, Essam A. and Kudo, Hiroyuki},
 journal = {Computer methods and programs in biomedicine},
 month = {May},
 note = {In computed tomography (CT), statistical iterative reconstruction (SIR) approaches can produce images of higher quality compared to the conventional analytical methods such as filtered backprojection (FBP) algorithm. Effective noise modeling and possibilities to incorporate priors in the image reconstruction problem are the main advantages that lead to continuous development of SIR methods. Oriented by low-dose CT requirements, several methods are recently developed to obtain a high-quality image reconstruction from down-sampled or noisy projection data. In this paper, a new prior information obtained from probabilistic atlas is proposed for low-dose CT image reconstruction.},
 pages = {119--136},
 title = {Probabilistic atlas prior for CT image reconstruction},
 volume = {128},
 year = {2016}
}