| Literature DB >> 32057617 |
Jia-Hui Cai1, Yuan He1, Xiao-Lin Zhong2, Hao Lei1, Fang Wang1, Guang-Hua Luo1, Heng Zhao3, Jin-Cai Liu4.
Abstract
Texture analysis is an emerging field that allows mathematical detection of changes in MRI signals that are not visible among image pixels. Alzheimer's disease, a progressive neurodegenerative disease, is the most common cause of dementia. Recently, multiple texture analysis studies in patients with Alzheimer's disease have been performed. This review summarizes the main contributors to Alzheimer's disease-associated cognitive decline, presents a brief overview of texture analysis, followed by review of various MR imaging texture analysis applications in Alzheimer's disease. We also discuss the current challenges for widespread clinical utilization. MR texture analysis could potentially be applied to develop neuroimaging biomarkers for use in Alzheimer's disease clinical trials and diagnosis.Entities:
Keywords: Alzheimer's disease; Machine learning; Magnetic Resonance Imaging; Texture Analysis
Year: 2020 PMID: 32057617 DOI: 10.1016/j.acra.2020.01.006
Source DB: PubMed Journal: Acad Radiol ISSN: 1076-6332 Impact factor: 3.173