Focal cortical dysplasia (FCD) is a common cause of epilepsy; the only treatment is surgery. Therefore, detecting FCD using noninvasive imaging technology can help doctors determine whether surgical intervention is required. Since FCD lesions are small and not obvious, diagnosing FCD through visual evaluations of magnetic resonance imaging (MRI) scans is difficult. The purpose of this study is to detect and segment histologically confirmed FCD lesions in images of normal fluid‐attenuated inversion recovery (FLAIR)‐negative lesions using convolutional neural network (CNN) technology.

中文翻译：

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使用卷积神经网络自动定位和分割FLAIR阴性患者的局灶性皮质发育异常。

局灶性皮质发育不良（FCD）是癫痫病的常见原因。唯一的治疗方法是手术。因此，使用无创成像技术检测FCD可以帮助医生确定是否需要手术干预。由于FCD病变很小且不明显，因此很难通过视觉评估磁共振成像（MRI）扫描来诊断FCD。这项研究的目的是使用卷积神经网络（CNN）技术在正常体液衰减型反转恢复（FLAIR）阴性病变的图像中检测并分割经组织学确认的FCD病变。