磁共振图像上多发性硬化症(MS)病变的自动计算机辅助检测

Z. Ekgi, Muhammed Emin Ozean, A. Aralaşmak, E. Dandıl, M. Çakiroglu
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引用次数: 1

摘要

多发性硬化症(MS)是一种中枢神经系统(CNS)疾病,由髓鞘损伤引起,髓鞘有助于确保大脑和脊髓之间的信息传递。多发性硬化症病变发生在髓鞘受损的患者身上。多发性硬化症病变的进展对检查疾病很重要。多发性硬化症病变通常由磁共振成像(MRI)确定并计划随访/治疗过程。在本研究中,提出了一种计算机辅助检测系统来诊断FLAIR MR图像上的MS病变。该系统使用模糊c均值(FCM)和形态学操作对MS病变进行分割。在本研究中,根据Jaccard指数对医生辅助检测到的病变和采用该系统检测到的病变进行了比较。在共90张MR图像的比较操作中,计算出相似率为91.2%。因此,它已被证明,提出的系统成功地检测MS病变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic computer-aided detection of Multiple Sclerosis (MS) lesions on MR images
Multiple Sclerosis (MS) is a central nervous system (CNS) disorders resulting from damage to the myelin sheath which helps to ensure the transmission of messages between the brain and spinal cord. MS lesions occur in patients with damage to the myelin sheath. Progression of MS lesions is important for examining the disease. MS lesions often Magnetic Resonance Imaging (MRI) is determined and planned the follow-up / treatment processes. In this study, a computer-aided detection system has been proposed to diagnose MS lesions on FLAIR MR images. The proposed system uses Fuzzy-C Means (FCM) and morphological operations for segmentation of MS lesions. In the study, the lesions detected by aid of physicians and the lesions detected by means of the proposed system have been compared according to the Jaccard index. Similarity rate in the comparison operation on a total of 90 MR images is calculated as 91.2%. Consequently, it has been shown that the proposed system successfully detected the MS lesions.
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