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A robust segmentation algorithm using morphological operators for detection of tumor in MRI

机译:使用形态学算子在MRI中检测肿瘤的鲁棒分割算法

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Image Denoising and Image Segmentation are the two major areas of the medical image processing. The main objective of this paper is to develop a robust segmentation algorithm inorder to detect tumor in 2D MRI brain images. Here we use image denoising as the preprocessing step as noise plays an important role incase of accuracy of affected area of the image, especially in medical diagnostics. To denoise the image, fourth order partial differential equation is employed. A seeded region growing segmentation is used to detect the tumor in MRI brain image. Also skull removal procedure is employed using morphological operators to increase the accuracy of brain tumor detection. This method detects the tumor in the brain image efficiently and also tested for several brain tumor images.
机译:图像去噪和图像分割是医学图像处理的两个主要领域。本文的主要目的是开发一种鲁棒的分割算法,以检测2D MRI脑图像中的肿瘤。这里,我们使用图像去噪作为预处理步骤,因为在图像受影响区域的准确性方面,噪声起着重要作用,尤其是在医学诊断中。为了对图像去噪,采用了四阶偏微分方程。种子区域生长分割法用于在MRI脑图像中检测肿瘤。还使用颅骨切除程序,使用形态学算子来提高脑肿瘤检测的准确性。这种方法可以有效地检测脑部图像中的肿瘤,并可以测试一些脑部肿瘤图像。

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