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

机译:使用形态过滤技术从脑MRIS的原发性肿瘤自动分割框架

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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:本文介绍了使用形态过滤技术从脑MRIS自动分割的新框架及其从脑MRIS的边界。 该方法使用T2加权和T1 Flair图像。 这种方法比现有方法更简单,更准确,更耗时少。 该方法由不同肿瘤类型,形状,图像强度,尺寸的50例患者进行测试,并产生更好的结果。 结果用放射科医师用地面真理图像验证。 肿瘤和边界检测的分割是重要的,因为它可用于外科计划,治疗计划,纹理分析,三维建模和体积分析。

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