Isa IS, Sulaiman SN, Mustapha M, Karim NK. Automatic contrast enhancement of brain MR images using Average Intensity Replacement based on Adaptive Histogram Equalization (AIR-AHE). Biocybernetics and Biomedical Engineering. 2017;37(1):24-34. (15)
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Development of the AIR-AHE algorithm for automatic contrast enhancement of FLAIR MRI using the imadjust and stretchlim functions |
The method showed good results along with other histogram equalization algorithms |
Isselmou AE, Zhang S, Xu G. A novel approach for brain tumor detection using MRI Images. J Biomedical Sci Eng. 2016;9(10):44-52. (17)
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Use of the high-pass median filter and histogram equalization to improve image quality |
The method improved image quality and provided excellent tumor segmentation results |
Sujan M, Alam N, Noman SA, Islam MJ. A Segmentation based Automated System for Brain Tumor Detection. IJCA. 2016;153(10):41-9. (32)
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Brain extraction on FLAIR images using MATLAB ® morphological operations, such as binarization, erosion, dilation and structuring elements |
The method contributed to better image enhancement results, and greater accuracy when compared with other algorithms in the literature |
Roy S, Maji P. A simple skull stripping algorithm for brain MRI. In: Eighth International Conference On Advances In Pattern Recognition (ICAPR) [Internet]. Kolkata: (IN); 2015 [cited 2019 Aug 20]. Available from: https://ieeexplore.ieee.org/abstract/document/7050671/ (33)
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Development of a method for skull stripping (S3) on T1-weighted images based on brain anatomy and image intensity |
The performance of the algorithm is compared to BET and BSE, with satisfactory results |
khandelwal P, Kaur G. Comparative study of different image enhancement technique. IJECT. 2016;7(2):116-21. (34)
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Comparison of contrast enhancement techniques (subtraction, contrast adjustment, erosion, gamma correction, inversion and thresholding) |
The erosion technique yielded the greatest results |
Kaur R, Chawla M, Khiva NK, Ansari MD. Comparative Analysis of Contrast Enhancement Techniques for Medical Images. Pertanika J Sci Technol. 2018;26(3):965-78. (35)
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Comparison of contrast enhancement techniques (neighborhood operation, median filter, imadjust and sigmoid function) |
The sigmoid function and the neighborhood operation provided the greatest results |
Shattuck DW, Sandor-Leahy SR, Schaper KA, Rottenberg DA, Leahy RM. Magnetic resonance image tissue classification using a partial volume model. Neuroimage. 2001;13(5):856-76. (36)
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Development of a method for skull stripping (BSE) on T1-weighted images using a border detector and a series of morphological operations |
A robust method, which contributes for GM and WM segmentation of the brain, respectively |
Smith SM. Fast robust automated brain extraction. Hum Brain Mapp. 2002;17(3):143-55. Review. (37)
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Development of a method for skull stripping (BET) on T1-weighted images |
A robust, precise method applied to a range of MRI sequences |
Roura E, Oliver A, Cabezas M, Vilanova JC, Rovira A, Ramió-Torrentà L, et al. MARGA: multispectral adaptive region growing algorithm for brain extraction on axial MRI. Comput Methods Programs Biomed. 2014 Feb 22;113(2):655-73. (38)
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Development of a method for skull stripping (MARGA) on axial views, based on the growth of the region |
The MARGA had superior results when compared with the BET and BSE approaches |
Somasundaram K, Mercina JH, Magesh Kalaiselvi ST. Brain Portion Extraction Scheme using Region Growing and Morphological Operation from MRI of Human Head Scans. IJCSE. 2018;6(4):298-302. (39)
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Development of a method for skull stripping based on growth of region and morphological operations (erosion, dilation and filling) |
The results of the method are superior to those of existing methods (BET and BSE) |
Kalavathi P, Prasath VB. Methods on Skull Stripping of MRI Head Scan Images—a Review. J Digit Imaging. 2016;29(3):365-79. Review. (40)
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Development of a method for brain extraction on T1-weighted MRI images based on median filter and morphological operations |
The method provided results comparable to those of the BET and BSE methods and showed that the median filter did not improve segmentation |