Multi-Dimensional Fuzzy C-Mean Considering Spatial Information for Brain MRI Segmentation

Majlesi Journal of Electrical Engineering

مقاله 6، دوره 8، شماره 1، خرداد 2014، صفحه 37-44   

نوع مقاله: Review Article

نویسندگان

Jamal Ghasemi^{* 1}؛ Mohammad Reza Karami Mollaei²؛ Reza Ghaderi³؛ Ali Hojjatoleslami⁴

¹Faculty of Engineering & Technology, University of Mazandaran

²Department of Electrical and Computer, Babol University of Technology, Babol, Iran

³Shahid Beheshti University, Tehran, Iran

⁴School of Computing, University of Kent, Canterbury, UK

چکیده

Due to artifacts, brain magnetic resonance image (MRI) segmentation is a complicated concern. This research work presents an image segmentation approach for brain magnetic resonance (MR) images. The proposed method is based on multi dimensional fuzzy C-mean. In this technique, different features of neighbouring pixels such as mean, standard deviation and singular value are extracted and then a multi dimensional feature vector is created in feature selection stage in which the best combination of extracted features is used. The created feature vector is used as an input to the multi dimensional FCM. The results have been evaluated with manual segmentation on two publicly available datasets متعدد الأبعاد غامض C یعنی وتضع فی اعتبارها المعلومات المکانیة لالدماغ بالرنین المغناطیسی التقسیم إلى شرائحبسبب القطع الأثریة والدماغ المغناطیسیة صورة الرنین (MRI) تجزئة هو مصدر قلق تعقیدا. یعرض هذا العمل البحثی نهج تجزئة صورة لدماغ بالرنین المغناطیسی (MR) الصور. وتستند هذه الطریقة المقترحة على التعددیة الأبعاد غامض C-المتوسط. فی هذه التقنیة، یتم استخراج میزات مختلفة من وحدات البکسل المجاورة مثل المتوسط والانحراف المعیاری وقیمة فریدة ثم یتم إنشاء ناقلات میزة الأبعاد المتعددة فی مرحلة اختیار میزة التی یتم استخدام أفضل مزیج من المیزات المستخرج. یتم استخدام ناقلات میزة خلق کمدخل إلى FCM متعددة الأبعاد. وقد تم تقییم النتائج مع تجزئة یدویة على اثنین من مجموعات البیانات المتاحة للجمهور多维模糊C均值考虑脑MRI分割空间信息贾马尔抽象由于文物，大脑磁共振成像（MRI）分割是一个复杂的问题。这项研究工作提出了大脑磁共振（MR）图像的图像分割方法。该方法是基于多维模糊C-均值。在该技术中，相邻像素如平均值，标准偏差和奇异值的不同特征提取，然后一个多维特征向量在特征选择阶段创建在其中使用的提取的特征的最佳组合。所创建的特征矢量被用作输入到多维FCM。结果已经与手动分段评估在两个公开获得的数据集

کلیدواژه‌ها

Brain MRI؛ en؛ Segmentation؛ Fuzzy c-mean

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