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Brain tumor segmentation from MRI using fractional sobel mask and watershed transform

机译:使用分数sobel面罩和分水岭变换从MRI进行脑肿瘤分割

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In this paper a novel brain tumor segmentation scheme using fractional order sobel mask and marker controlled watershed transform is proposed. To obtain the bright tumor region, regional maxima operation is performed on morphological preprocessed input T2-weighted MR image. The output regional maxima image is taken as an internal marker. Distance transform based watershed transform is applied on regional maxima image, the watershed ridge lines are used as external marker. Now, the fractional sobel mask of order a=0.3 is applied on input T2-weighted MR brain image to obtain gradient magnitude image. The segmentation of tumor region is achieved by using the watershed transform of gradient magnitude image with the help of derived internal and external markers. Region of interest (ROI) is selected to get the final segmented tumor image. Simulations are performed on images taken from the BRATS-2013 dataset for different values of a. For a = 0.3 values of accuracy, sensitivity and specificity performance parameters are comparable to other schemes compared. Moreover, fractional order a provides additional degree of freedom in optimizing the segmentation results. Proposed scheme can be used to segment other types of tumors and also for segmentation of CT images.
机译:本文提出了一种使用分数阶sobel掩码和标记控制的分水岭变换的新型脑肿瘤分割方案。为了获得明亮的肿瘤区域,对形态学预处理的输入T2加权MR图像执行区域最大值操作。输出的区域最大值图像被用作内部标记。基于距离变换的分水岭变换应用于区域最大值图像,分水岭脊线用作外部标记。现在,在输入的T2加权MR脑图像上应用阶数为a = 0.3的分数sobel掩模以获得梯度幅度图像。通过使用梯度幅值图像的分水岭变换,借助派生的内部和外部标记,可以实现肿瘤区域的分割。选择感兴趣区域(ROI)以获得最终分割的肿瘤图像。对从BRATS-2013数据集获取的图像针对a的不同值执行模拟。对于a = 0.3的准确度值,灵敏度和特异性性能参数可与其他比较方案进行比较。此外,分数阶a在优化分割结果时提供了额外的自由度。提出的方案可用于分割其他类型的肿瘤,也可用于CT图像分割。

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