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Patient-specific tumor prognosis prediction via multimodality imaging

机译:通过多模成像的患者特异性肿瘤预后预测

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This paper proposes an approach to advance the utility of physical modeling techniques for medical applications by correlating finite element based models with the mechanical anatomy characteristic of a clinical patient. A methodology is presented to model the patient-specific mechanical response of brain tissue in vivo. The resultant model is parameterized in terms of clinical CT and MRI imaging sequences acquired for each patient. Applications of the proposed technique to the areas of brain tumor growth modeling and predicting tissue shifts during stereotactic neurosurgery, are described. Results are presented for an implementation of our approach to the problem of predictive brain tumor modeling.
机译:本文提出了一种通过将基于元素的模型与临床患者的机械解剖学相关,提出了一种推进物理建模技术的实用性。提出了一种方法来模拟体内脑组织的患者特异性机械响应。结果模型在为每位患者获得的临床CT和MRI成像序列方面进行参数化。描述了所提出的技术对脑肿瘤生长建模和预测组织在立体神经外科期间的基位的应用。提出了我们对预测性脑肿瘤建模问题的方法的实施。

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