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دانلود رایکان مقاله انگلیسی ISI با موضوع ارزیابی k-Means و بخش بندی تصاویر MR از مغز و فازی C-Means

عنوان فارسی مقاله:

ارزیابی k-Means و بخش بندی تصاویر MR از مغز و فازی C-Means

عنوان انگلیسی مقاله:

Evaluation of k-Means and fuzzy C-means segmentation on MR images of brain

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4. Conclusion

The efficacy of FCM and k-Means, with histogram guided initialization, was analyzed on T1 contrast axial plane MR images of GBM-edema complex. FCM could identify two tissue classes and background. It merged GM, CSF and necrotic focus into one class and WM and perifocal edema into another. FCM produced three empty clusters in first two test images and two in the last one. k-Means could identify CSF, GM, WM, necrosis, edema and background region. But, certain parts of the WM were clustered with enhancing edema and vice versa. This cross talk occurs between CSF, necrosis and GM also. This happens as the intensity features of the edema and certain parts of WM are perfectly equal. Similarly, certain parts of CSF, GM and necrosis also shares homogenous intensity features. Fully automated segmentation of GBM, hence would be intricate and intensity based segmentation would not be viable for MR images of GBM-edema complex