Content‐oriented sparse representation ( COSR ) for  CT  denoising with preservation of texture and edge | Zendy

Xie Huiqiao | Zendy; Niu Tianye | Zendy; Tang Shaojie | Zendy; Yang Xiaofeng | Zendy; Kadom Nadja | Zendy; Tang Xiangyang | Zendy

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Content‐oriented sparse representation ( COSR ) for CT denoising with preservation of texture and edge

Author(s) -

Xie Huiqiao,

Niu Tianye,

Tang Shaojie,

Yang Xiaofeng,

Kadom Nadja,

Tang Xiangyang

Publication year - 2018

Publication title -

medical physics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.473

H-Index - 180

eISSN - 2473-4209

pISSN - 0094-2405

DOI - 10.1002/mp.13189

Subject(s) - noise reduction , imaging phantom , sparse approximation , artificial intelligence , noise (video) , computer science , pattern recognition (psychology) , image quality , similarity (geometry) , segmentation , computer vision , representation (politics) , signal to noise ratio (imaging) , enhanced data rates for gsm evolution , mathematics , image (mathematics) , nuclear medicine , medicine , telecommunications , politics , political science , law

Denoising has been a challenging research subject in medical imaging, since the suppression of noise conflicts with the preservation of texture and edges. To address this challenge, we develop a content-oriented sparse representation (COSR) method for denoising in computed tomography (CT).

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