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AN INTEGRATED APPROACH TO LOCALIZE EPILEPTIC FOCI USING RELATIVE SPECT SUBTRACTION

机译:一种使用相对谱相减法定位癫痫病灶的综合方法

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Accurate epileptic focus localization using SPECT images has proven itself to be a challenging endeavor. Firstly, this is partly due to the fact that radiopharmaceuticals such as hexamethylpropylene amine oxime (HMPAO) quantitatively underestimate large blood flows; this may lead to SPECT images that do not reflect the true physiological conditions in the brain. This often leads to subtracted SPECT images that contain non-distinct epileptic foci. Therefore, better methods of SPECT image analysis need to be devised that can overcome this quantitative defect. The relative change subtraction method proposed alleviates the burden imposed by this problem. Secondly, the analysis of SPECT images has traditionally been performed by physicians and is often tune-consuming and prone to error. Though software packages exist to aid this process in distinct phases, an integrated and fully automated approach is a more desirable outcome. Interactivity will be provided through a visual interface for medical expert feedback in the decision-making process. To meet such desired outcomes, an integrated algorithm has been designed to automate the process of SPECT image analysis so that minimal human intervention is required.
机译:使用SPECT图像进行精确的癫痫病灶定位已证明是一项具有挑战性的工作。首先,这部分是由于诸如六甲基丙烯胺肟(HMPAO)之类的放射性药物在数量上低估了大流量的事实。这可能会导致SPECT图像无法反映大脑的真实生理状况。这通常会导致包含非明显癫痫灶的SPECT图像相减。因此,需要设计出更好的SPECT图像分析方法来克服这种定量缺陷。提出的相对变化减法减轻了该问题带来的负担。其次,传统上,SPECT图像的分析是由医生进行的,并且通常很费劲并且容易出错。尽管存在用于在不同阶段帮助该过程的软件包,但更理想的结果是采用集成且完全自动化的方法。交互性将通过可视界面提供,以在决策过程中为医学专家提供反馈。为了满足这些期望的结果,已经设计了一种集成算法来自动执行SPECT图像分析过程,因此需要最少的人工干预。

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