Automatic contrast enhancement of brain MR images using Average Intensity Replacement based on Adaptive Histogram Equalization (AIR-AHE)

• Autorzy: Isa I. S. , Sulaiman S. N. , Mustapha M. , Karim N. K. A.

Identyfikatory

DOI

10.1016/j.bbe.2016.12.003

• Języki publikacji: EN

Abstrakty

EN

Medical imaging is the most established technique of visualizing the interior of the human body without the risk of the non-invasive effect. This technology is designed to produce images, and it is also capable of representing information about the screening location. In MRI imaging, the poor image quality particularly the low contrast image may provide insufficient data for the visual interpretation of such affected locations. Therefore, the need of image enhancement arises to improve image visions and also to computationally support the image processing technique. In general, conventional contrast enhancement methods may work well for some images. However, in MRI brain image, there are often more complex situations where the WMH signal is high but it may mistakenly be considered as other brain tissues such as CSF. With the motivation to classify the most possible WMH regions, this paper proposes a novel image contrast algorithm of WMH enhancement for MRI image. This algorithm is also known as the Average Intensity Replacement – Adaptive Histogram Equalization (AIR-AHE). The proposed algorithm is applied to the FLAIR image based on the intensity adjustment and contrast mapping techniques. The proposed algorithm for the image enhancement is superior to the existing methods by using image evaluation quantitative methods of PSNR, average gradient values and MSE. Furthermore, the edge information pertaining to the potential WMH regions can effectively increase the accuracy of the results.

Słowa kluczowe

EN

MRI image; contrast enhancement; contrast algorithm; WMH signal; intensity based

PL

obraz MRI; wzmocnienie kontrastowe; WMH

• 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. 1
• Strony: 24--34
• Opis fizyczny: Bibliogr. 24 poz., rys., tab.

Twórcy

autor

Isa I. S.

• Faculty of Electrical Engineering, Universiti Teknologi MARA, Pulau Pinang, Malaysia

autor

Sulaiman S. N.

• Faculty of Electrical Engineering, Universiti Teknologi MARA, Pulau Pinang, Malaysia

autor

Mustapha M.

• School of Medical Science, Universiti Sains Malaysia, Kelantan, Malaysia

autor

Karim N. K. A.

• Imaging Unit, Advanced Medical and Dental Institute, Universiti Sains Malaysia, Pulau Pinang, Malaysia

Bibliografia

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Uwagi

PL

W opisie bibliograficznym brak pozycji nr 12.

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).