首页> 外文会议>2017 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization >Self-organizing maps as a tool for segmentation of Magnetic Resonance Imaging (MRI) of relapsing-remitting multiple sclerosis
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Self-organizing maps as a tool for segmentation of Magnetic Resonance Imaging (MRI) of relapsing-remitting multiple sclerosis

机译:自组织图作为复发-缓解型多发性硬化症磁共振成像(MRI)分割的工具

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摘要

Multiple Sclerosis (MS) is the most prevalent demyelinating disease of the Central Nervous System, being the Relapsing-Remitting (RRMS) its most common subtype. We explored here the viability of use of Self Organizing Maps (SOM) to perform automatic segmentation of MS lesions apart from CNS normal tissue. SOM were able, in most cases, to successfully segment MRIs of patients with RRMS, with the correct separation of normal versus pathological tissue especially in supratentorial acquisitions, although it could not differentiate older from newer lesions.
机译:多发性硬化症(MS)是中枢神经系统最普遍的脱髓鞘疾病,是其最常见的亚型-复发缓解型(RRMS)。我们在这里探讨了使用自组织图(SOM)进行除CNS正常组织之外的MS病变自动分割的可行性。在大多数情况下,SOM能够成功分割RRMS患者的MRI,正确分离正常组织与病理组织,特别是在幕上采集中,尽管它无法区分旧病灶与新病灶。

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