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Tumor Boundary Extraction Using Intensity, Texture and Gradient Vector

机译:使用强度,纹理和梯度向量提取肿瘤边界提取

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In medical research study doctors and radiologists face lot of complexities in analyzing the brain tumors in Magnetic Resonance (MR) images. Brain tumor detection is difficult due to amorphous tumor shape and overlapping of similar tissues in nearby region. So, radiologists require one such clinically viable solution which helps in automatic segmentation of tumor inside brain MR image. Initially, segmentation methods were used to detect tumor, by dividing the image into segments but causes loss of information. In this paper, a hybrid method is proposed which detect Region of Interest (ROI) on the basis of difference in intensity values and texture values of tumor region using nearby tissues with Gradient Vector Flow (GVF) technique in the identification of ROI. Proposed approach uses both intensity and texture values for identification of abnormal section of the brain MR images. Experimental results show that proposed method outperforms GVF method without any loss of information.
机译:在医学研究中,研究医生和放射科学家在分析磁共振(MR)图像中的脑肿瘤时面临着大量复杂性。由于无定形肿瘤形状和附近地区的类似组织重叠,脑肿瘤检测难以困难。因此,放射科医师需要一种这样的临床活性溶液,其有助于在脑MR图像内部肿瘤的自动分割。最初,通过将图像划分为片段来初始化分割方法来检测肿瘤,但导致信息损失。在本文中,提出了一种混合方法,其基于识别ROI的附近组织的肿瘤区强度值和肿瘤区纹理值的差异和质地值的差异检测感兴趣区域(ROI)。所提出的方法使用强度和纹理值来识别脑MR图像的异常部分。实验结果表明,提出的方法优于GVF方法,无需任何信息损失。

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