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

Ivonne M. Avila-Mora, S. Mendoza, Kimberly García, R. Delgado-Hernández, O. Marrufo-Melendez, D. S. Juan-Orta
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Abstract

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.
通过T2/MRI序列的强度分析发现大脑皮层的疤痕
如今,检测大脑皮层的疤痕通常需要神经学家和放射科医生手工操作。这是一项艰巨的任务,因为必须克服多个问题,从用于获取大脑皮层图像的设备的不良校准到MRI(磁共振成像)序列的空间和几何畸变等几个错误。这些问题在放射外科等需要高空间精度的活动中引起严重的并发症。通过实现能够分析MRI序列的算法,可以简单而成功地自动检测大脑皮层中的疤痕。此外,疤痕的自动检测减少了人类解释的主观性,并作为支持疾病诊断的工具。本文提出了一种新的大脑皮层疤痕自动检测方法。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序列的强度分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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