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Multi-parametric tissue characterization of brain neoplasms and their recurrence using pattern classification of MR images

机译:使用MR图像的模式分类对脑肿瘤及其复发进行多参数组织表征

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摘要

Rationale and Objectives:Treatment of brain neoplasms can greatly benefit from better delineation of bulk neoplasm boundary and the extent and degree of more subtle neoplastic infiltration. MRI is the primary imaging modality for evaluation before and after therapy, typically combining conventional sequences with more advanced techniques like perfusion-weighted imaging and diffusion tensor imaging (DTI). The purpose of this study is to quantify the multi-parametric imaging profile of neoplasms by integrating structural MRI and DTI via statistical image analysis methods, in order to potentially capture complex and subtle tissue characteristics that are not obvious from any individual image or parameter.
机译:原理和目的:更好地划定肿块肿瘤边界以及更细微的肿瘤浸润的程度和程度,可以极大地治疗脑肿瘤。 MRI是治疗前后评估的主要成像方式,通常将常规序列与更先进的技术(如灌注加权成像和扩散张量成像(DTI))结合起来。这项研究的目的是通过统计图像分析方法整合结构性MRI和DTI来量化肿瘤的多参数成像图谱,以便潜在地捕获从任何单个图像或参数中都不明显的复杂而微妙的组织特征。

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