Age Prediction based on Brain MRI Images using Extreme Learning Machine

被引:10
|
作者
Afshar, Leila Keshavarz [1 ]
Sajedi, Hedieh [1 ,2 ]
机构
[1] Univ Tehran, Coll Sci, Sch Math Stat & Comp Sci, Tehran, Iran
[2] Inst Res Fundamental Sci IPM, Sch Comp Sci, POB 19395-5746, Tehran, Iran
来源
2019 7TH IRANIAN JOINT CONGRESS ON FUZZY AND INTELLIGENT SYSTEMS (CFIS) | 2019年
关键词
MRI; Brain Age; Machine Learning; CLASSIFICATION;
D O I
10.1109/cfis.2019.8692156
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Age Prediction, which means setting up a machine learning system, defined by using different sets of data for training, and then the estimation of the actual age of humans, is a subject that has been studied in recent years. To achieve this, researchers have been experimenting with various body components, such as DNA, speech signals, medical images, facial images, etc. Recent researches show that brain structure changes with age or psychiatric disorders. So a useful tool for estimating the age of humans is the brain's MRI images. Brain Magnetic Resonance Imaging (MRI) use radio waves and a robust magnetic field to create detailed images of the organs and tissues within the body. In this paper, the age of humans is predicted based on brain MRI images. To extract T1-MRI features, two different methods are proposed, then to estimate age, Extreme Learning Machine (ELM) is employed. Given that the amount of computations needed in this method and the time required to age estimation is low, the proposed method has acceptable performance.
引用
收藏
页码:1 / 5
页数:5
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