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Finding scars in the cerebral cortex through the analysis of intensities in T2/MRI sequences

机译:通过分析T2 / MRI序列的强度发现大脑皮层疤痕

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Nowadays, the detection of scars in the cerebral cortex usually involves a manual process performed by neurologists and radiologists. It is a difficult task to carry out, since multiple troubles have to be overcome, from bad calibration of the equipment used to get the cerebral cortex images to several errors, such as spacial and geometrical distortions of MRI (Magnetic Resonance Imaging) sequences. These problems present serious complications in activities such as radiosurgery, which requires high spacial accuracy. Through the implementation of algorithms capable of analyzing MRI sequences, it is possible to automatically detect scars in the cerebral cortex in an easy and successful manner. In addition, the automatic detection of scars decreases the subjectivity of human interpretations and serves as a tool to support diagnoses of diseases. In this paper, a new methodology to automatically detect scars in the cerebral cortex is proposed. The main goal of this methodology is to facilitate the analysis of intensities in T2/MRI sequences by using the region growing and thresholds, as well as artificial neural networks.
机译:如今,大脑皮层疤痕的检测通常涉及由神经科医生和放射科医生执行的手动过程。这是一项艰巨的任务,因为必须克服多种麻烦,从用于获取大脑皮层图像的设备的标定不正确到几个错误,例如MRI(磁共振成像)序列的空间和几何失真。这些问题在诸如放射外科手术之类的活动中造成严重的并发症,这要求高的空间精度。通过执行能够分析MRI序列的算法,可以轻松,成功地自动检测大脑皮层中的疤痕。另外,疤痕的自动检测降低了人类解释的主观性,并成为支持疾病诊断的工具。本文提出了一种自动检测大脑皮层疤痕的新方法。该方法的主要目标是通过使用区域增长和阈值以及人工神经网络来促进T2 / MRI序列强度的分析。

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