Fuzzy Curvelet Based Fully Automated Segmentation of Brain from MR Images

Jaffar, M. Arfan; Aini, Qurat-ul-Ain; Masood, Sohail; Iqbal, Amjad; Javed, Arshad; Mirza, Anwar M.

doi:10.1109/csa.2009.5404276

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B Segmentation K-means1

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2014

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“…This distance is measured in terms of Euclidean. Fuzzy C-Means Clustering (FCM): FCM [11], [13] is frequently applied in numerous areas like pattern recognition, classification, bioinformatics, image analysis and segmentation etc. In FCM clustering technique, a membership degree is assigned to each data point which specifies belongingness of a data point to a specific class.…”

Section: B Segmentation K-meansmentioning

confidence: 99%

Enhancement of Magnetic Resonance Images Using Soft Computing Based Segmentation

Javed¹,

Wang²,

Alenezi³

et al. 2014

IJMLC

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Abstract-Segmentation is the process of extracting points, lines or regions, which are then used as inputs for complementary tasks such as registration, measurement, movement analysis, visualization , etc in MRI. The noise in MR images degrades the image quality and also affect on the segmentation process which can lead to wrong diagnosis. The main aim of this study is to suggest a system to enhance the quality of the human brain MRI. In the proposed system, median filter is used for image enhancement of brain MRI and fuzzy c-means for segmentation purpose. The proposed method is completely automatic that is there is no user involvement in the proposed system. The system is tested on different kinds of brain MR images and proved robust against noise as well as segments the images fast with improvements.Index Terms-Dunn's index, fuzzy c-means (FCM), image segmentation, median filter.

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Section: B Segmentation K-meansmentioning

confidence: 99%