Medical image denoising via optimal implementation of non-local means on hybrid parallel architecture. Issue 129 (June 2016)

• Record Type: Journal Article
• Authors: Nguyen, Tuan-Anh; Nakib, Amir; Nguyen, Huy-Nam
• Is Part Of: Computer methods and programs in biomedicine. Issue 129(2016)
• Page Start: 29
• Page End: 39
• Publication Date: 2016-06
• Subjects: Parallel computing -- High performance computing -- Image denoising -- Image enhancement; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2016.02.002
• Languages: English
• ISSNs: 0169-2607

Abstract

Abstract : Highlights: The symmetric weight scheme allows reducing the computation time by a factor 2. Our implementation of NL-Means reduces computation time by a factor of 510. Self-adaptive method is proposed to allow the filter to be more efficient. Abstract: The Non-local means denoising filter has been established as gold standard for image denoising problem in general and particularly in medical imaging due to its efficiency. However, its computation time limited its applications in real world application, especially in medical imaging. In this paper, a distributed version on parallel hybrid architecture is proposed to solve the computation time problem and a new method to compute the filters' coefficients is also proposed, where we focused on the implementation and the enhancement of filters' parameters via taking the neighborhood of the current voxel more accurately into account. In terms of implementation, our key contribution consists in reducing the number of shared memory accesses. The different tests of the proposed method were performed on the brain-web database for different levels of noise. Performances and the sensitivity were quantified in terms of speedup, peak signal to noise ratio, execution time, the number of floating point operations. The obtained results demonstrate the efficiency of the proposed method. Moreover, the implementation is compared to that of other techniques, recently published in the literature.