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Automatic white matter lesion detection and segmentation on Magnetic Resonance Imaging: A review of past and current state-of-the-art

Ong, Kok Haur and Shamuddin, Siti Mariyam and Sulaiman, Sarina and Ali, Aida and Mohd Zain, Norzaini Rose and Hang, See Pheng (2018) Automatic white matter lesion detection and segmentation on Magnetic Resonance Imaging: A review of past and current state-of-the-art. International Journal of Advances in Soft Computing and its Applications, 10 (3). pp. 20-53. ISSN 2074-8523

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Abstract

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.

Item Type:Article
Uncontrolled Keywords:automated segmentation, brain MRI, white matter hyperintensities
Subjects:Q Science > Q Science (General)
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Science
ID Code:86609
Deposited By: Yanti Mohd Shah
Deposited On:30 Sep 2020 08:44
Last Modified:30 Sep 2020 08:44

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