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Automatic segmentation framework for primary tumors from brain MRIs using morphological filtering techniques

机译:使用形态学过滤技术从脑部MRI自动分割原发肿瘤的框架

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This paper describes a novel framework for automatic segmentation of primary tumors and its boundary from brain MRIs using morphological filtering techniques. This method uses T2 weighted and T1 FLAIR images. This approach is very simple, more accurate and less time consuming than existing methods. This method is tested by fifty patients of different tumor types, shapes, image intensities, sizes and produced better results. The results were validated with ground truth images by the radiologist. Segmentation of the tumor and boundary detection is important because it can be used for surgical planning, treatment planning, textural analysis, 3-Dimensional modeling and volumetric analysis.
机译:本文介绍了一种使用形态学过滤技术从脑部MRI自动分割原发肿瘤及其边界的新颖框架。此方法使用T2加权图像和T1 FLAIR图像。与现有方法相比,此方法非常简单,更准确且耗时更少。该方法由五十名不同肿瘤类型,形状,图像强度,大小的患者测试,并产生了更好的结果。放射科医生用地面真实图像验证了结果。肿瘤的分割和边界检测很重要,因为它可用于手术计划,治疗计划,纹理分析,三维建模和体积分析。

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