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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-05b042e3-9ee7-498c-8840-185902bc8708

Czasopismo

Biocybernetics and Biomedical Engineering

Tytuł artykułu

An objective method to identify optimum clip-limit and histogram specification of contrast limited adaptive histogram equalization for MR images

Autorzy Joseph, J.  Sivaraman, J.  Periyasamy, R.  Simi, V. R. 
Treść / Zawartość http://www.ibib.waw.pl/pl/wydawnictwa/biocybernetics-and-biomedical-enginering-bbe/bbe-tomy http://www.journals.elsevier.com/biocybernetics-and-biomedical-engineering/
Warianty tytułu
Języki publikacji EN
Abstrakty
EN In contrast limited adaptive histogram equalization (CLAHE), the selection of tile size, clip-limit and the distribution which specify desired shape of the histogram of image tiles is paramount, as it critically influences the quality of the enhanced image. The optimal value of these parameters devolves on the generic of the image to be enhanced and usually they are selected empirically. In this paper, the degradation of intensity, textural and geometric features of the medical image with respect to the variation in clip-limit and specified histogram shape is analyzed. The statistical indices used to quantify the feature degradation are Absolute Mean Brightness Error (AMBE), Absolute Deviation in Entropy (ADE), Peak Signal to Noise Ratio (PSNR), Variance Ratio (VR), Structural Similarity Index Matrix (SSIM) and Saturation Evaluation Index (SEI). The images used for the analysis are axial plane MR images of magnetic resonance spectroscopy (MRS), under gradient recalled echo (GRE), diffusion weighted imaging (DWI) 1000b Array Spatial Sensitivity Encoding Technique (ASSET), T2 Fluid Attenuation Inversion Recovery (FLAIR) and T1 Fast Spin-Echo Contrast Enhanced (FS-ECE) series of pre-operative Glioblastoma-edema complex. The experimental analysis was performed using Matlab®. Results show that for MR images the exponential histogram specification with a clip-limit of 0.01 is found to be optimum. At optimum clip-limit, the mean of SSIM exhibited by the Rayleigh, uniform and exponential histogram specification were found to be 0.7477, 0.7946 and 0.8457, for ten sets of MR images and mean of variance ratio are 1.242, 2.0316 and 1.7711, respectively.
Słowa kluczowe
EN absolute deviation in entropy   absolute mean brightness error   clip limit   tile size   peak signal to noise ratio   saturation evaluation index  
Wydawca Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences
Elsevier
Czasopismo Biocybernetics and Biomedical Engineering
Rocznik 2017
Tom Vol. 37, no. 3
Strony 489--497
Opis fizyczny Bibliogr. 20 poz., rys., tab., wykr.
Twórcy
autor Joseph, J.
autor Sivaraman, J.
  • Department of Biomedical Engineering, Vel Tech Multi Tech Engineering College, Avadi, Chennai 600062, India, mountshiva@gmail.com
autor Periyasamy, R.
  • Department of Biomedical Engineering, National Institute of Technology, Raipur, India
autor Simi, V. R.
  • Department of Computer Science & Engg., KVM College of Engineering & Information Technology, Kerala, India, simijijeesh@gmail.com
Bibliografia
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[10] Ahmad SAB, Taib MN, Khalid NEA, Ahmad ABT. The effect of sharp contrast-limited adaptive histogram equalization (SCLAHE) on intra-oral dental radiograph images. Proc of IEEE EMBS Conf on Biomed Eng Sci; 2010. pp. 400–5.
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[15] Ravishankar M, Mohan S. Optimized histogram based contrast limited enhancement for mammogram images. ACEEE Int J Inf Technol 2013;3(1):5–8.
[16] Mohan S, Mahesh TR. Particle swarm optimization based contrast limited enhancement for mammogram images. Proc of 7th Int Conf on Intel Syst and Con; 2013. pp. 384–8.
[17] Wang Z, Bovik AC, Sheikh HR, Simoncelli EP. Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 2014;13:600–12.
[18] Huynh-Thu Q, Ghanbari M. Scope of validity of PSNR in image/video quality assessment. Electron Lett 2008;44:800–1.
[19] Saleem A, Beghdadi A, Boashash B. Image fusion-based contrast enhancement. Eurasip J Image Video Process 2012;10:1–17.
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Uwagi
PL Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Kolekcja BazTech
Identyfikator YADDA bwmeta1.element.baztech-05b042e3-9ee7-498c-8840-185902bc8708
Identyfikatory
DOI 10.1016/j.bbe.2016.11.006