title: The Application of Wavelet-Domain Hidden Markov Tree Model in Diabetic Retinal Image Denoising.
abstract: The wavelet-domain Hidden Markov Tree Model can properly describe the dependence and correlation of fundus angiographic images' wavelet coefficients among scales. Based on the construction of the fundus angiographic images Hidden Markov Tree Models and Gaussian Mixture Models, this paper applied expectation-maximum algorithm to estimate the wavelet coefficients of original fundus angiographic images and the Bayesian estimation to achieve the goal of fundus angiographic images denoising. As is shown in the experimental result, compared with the other algorithms as mean filter and median filter, this method effectively improved the peak signal to noise ratio of fundus angiographic images after denoising and preserved the details of vascular edge in fundus angiographic images.
authors.affiliation: Department of Radiology, Taishan Medical University, Taian 271016, P.R. China.
authors.forename: Dong
authors.initials: D
authors.lastname: Cui
authors.affiliation: Ophthalmology, Hospital of Traditional Chinese Medicine, Taian 271000, P.R. China.
authors.forename: Minmin
authors.initials: M
authors.lastname: Liu
authors.affiliation: Ophthalmology, Hospital Affiliated to Taishan Medical University, Taian 271000, P.R. China.
authors.forename: Lei
authors.initials: L
authors.lastname: Hu
authors.affiliation: Ophthalmology, Hospital of Traditional Chinese Medicine, Taian 271000, P.R. China.
authors.forename: Keju
authors.initials: K
authors.lastname: Liu
authors.affiliation: Department of Radiology, Taishan Medical University, Taian 271016, P.R. China.
authors.forename: Yongxin
authors.initials: Y
authors.lastname: Guo
authors.affiliation: Department of Radiology, Taishan Medical University, Taian 271016, P.R. China.
authors.forename: Qing
authors.initials: Q
authors.lastname: Jiao
keywords: Fundus images; HIDDEN Markov Tree Model (HMT Model); image denoising; wavelet transform