Adaptive Real-Time Removal of Impulse Noise in Medical Images.
Noise is an important factor that degrades the quality of medical images. Impulse noise is a common noise caused by malfunctioning of sensor elements or errors in the transmission of images. In medical images due to presence of white foreground and black background, many pixels have intensities simi...
| Publicado en: | Journal of Medical Systems Vol. 42; no. 11; pp. 1 - 2 |
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| Autores principales: | , , , , , , |
| Formato: | diagnostic images tables/charts Journal Article |
| Publicado: |
Springer Nature
Nov2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=132813848&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 132813848 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Nov2018 vid: 42 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 132813848 132813848 132813848 10.1007/s10916-018-1074-7 132813848 ppf: 1 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Adaptive Real-Time Removal of Impulse Noise in Medical Images. aug: au: HosseinKhani, Zohreh Hajabdollahi, Mohsen Karimi, Nader Soroushmehr, Reza Shirani, Shahram Najarian, Kayvan Samavi, Shadrokh affil: Department of Electrical and Computer Engineering, Isfahan University of Technology, 84156-83111, Isfahan, Iran sug: subj: Image Processing, Computer Assisted Methods Signal Processing, Computer Assisted Methods Systems Implementation Diagnostic Imaging Equipment and Supplies Algorithms Image Enhancement Computer Hardware Software Computer Simulation Noise Brain Anatomy and Histology Magnetic Resonance Imaging ab: Noise is an important factor that degrades the quality of medical images. Impulse noise is a common noise caused by malfunctioning of sensor elements or errors in the transmission of images. In medical images due to presence of white foreground and black background, many pixels have intensities similar to impulse noise and hence the distinction between noisy and regular pixels is difficult. Therefore, it is important to design a method to accurately remove this type of noise. In addition to the accuracy, the complexity of the method is very important in terms of hardware implementation. In this paper a low complexity de-noising method is proposed that distinguishes between noisy and non-noisy pixels and removes the noise by local analysis of the image blocks. All steps are designed to have low hardware complexity. Simulation results show that in the case of magnetic resonance images, the proposed method removes impulse noise with an acceptable accuracy. pubtype: Academic Journal doctype: diagnostic images tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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