학술논문

Magnetic resonance signal processing tool for diagnostic classification
Document Type
Conference
Source
2016 IEEE 36th International Conference on Electronics and Nanotechnology (ELNANO) Electronics and Nanotechnology (ELNANO), 2016 IEEE 36th International Conference on. :175-179 Apr, 2016
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Power, Energy and Industry Applications
Signal Processing and Analysis
Iron
Magnetic resonance imaging
Ions
Alzheimer's disease
Image reconstruction
proton spin-spin relaxation
spin-spin relaxation time
iron accumulation
signal processing
magnetic resonance imaging
Language
Abstract
Since tissue function has an influence on the structure and integrity, measures that characterize the changes of tissue content allow one to detect the tissue loss or functional damage. The purpose of this investigation is to localize tissue with iron overload and illustrate its simple detection and quantification at magnetic resonance images. This article describes a simple, novel and quantitative method to calculate an ion excess from processing of magnetic resonance signals. After description of iron overload in brain tissues and the magnetic resonance signal processing method the relationships between iron deposition and Alzheimer's disease stages are presented. Magnetic resonance images of independently diagnosed subjects used for assessment of tissue iron. The result of brain tissue iron deposition was the highest in Alzheimer's disease cases and the lowest in normal subjects. Proposed techniques of signal processing allow robust estimates of organ iron concentration with functional correlations in patients with iron overload.