文章基本信息

标题：Automatic white matter lesion detection and segmentation on Magnetic Resonance Imaging: A review of past and current state-of-the-art
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作者：K. H. Ong ; S. M. Shamsuddin ; S. Sulaiman 等
期刊名称：International Journal of Advances in Soft Computing and Its Applications
印刷版ISSN：2074-8523
出版年度：2018
卷号：10
期号：3
出版社：International Center for Scientific Research and Studies
摘要：White matter lesion (WML) is an abnormal tissue occurring in white matter. It indicated the damage of the myelin sheath that used to surround the axon of a neurone. This resulting neurological and vascular disorder occur in the patient, also commonly developed in the healthy brain of elderly. Magnetic Resonance Imaging is a non-invasive medical equipment preferred choice by the clinician to diagnose and observed the injury of brain tissue. However, WML quantitative assessment and analyse on the large volume of MR imaging is a challenge. In this paper, we provide an intensive review of the past and recent WML delineation and detection methods. This review included visual scoring assessment, a common preprocessing step for WML segmentation, false positive elimination, and the latest automatic WML segmentation approaches will be presented.
关键词：Automated segmentation; brain MRI; white matter lesion; white matter hyperintensities