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Understanding MRI Noise Processes and Signal Sources: A Comprehensive Overview

This lecture focuses on the intricate processes underlying noise in MRI, highlighting the role of dipole moments, magnetic fields, and proton dynamics. Explore how the source of the signal, often linked to proton or water MRI, interacts with magnetic field strengths (B0) and thermal noise. Delve into the phenomena of Brownian motion and its significance in detecting signals amidst noise, while examining probability distributions such as Rayleigh and Rician. This overview is essential for understanding signal-to-noise ratio (SNR) dependencies in high-field MRI techniques.

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Understanding MRI Noise Processes and Signal Sources: A Comprehensive Overview

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  1. Lecture 23: 1. MRI noise processes MP574

  2. Dipole Moments from Entire Sample Magnetic Field (B0) Magnetic Field (B0) m m Positive Orientation Negative Orientation

  3. Source of Signal • Proton or Water MRI • Bo Magnetic Field • Proton Nucleus • S = ±ħ/2 rg 2 2 h DE D µ = E M B z o 4 kT

  4. z B1(t) F = w AB g cos( t ) 1 L g 2 w Ah B Ah = µ w w = w o L V ( t ) S ( t ) g sin( t ) g sin( t ) y L L L kT kT x Detected Signal

  5. Brownian Motion • Brownian Motion Conditions: • x0= 0 • x(t) is a continuous random variable • Increments x(t1) and x(t2) are statistically independent and normally distributed http://en.wikipedia.org/wiki/Wiener_process

  6. Brownian Motion

  7. Rp Rc Johnson or “Thermal” Noise Electrical Resistance of Coil Patient Resistance Thermal noise in patient dominant at high field strengths

  8. Johnson or “Thermal” Noise on both I and Q channels I = “in phase” Q = “quadrature” or 90o out of phase Imaginary Real

  9. Independent Realizations of GWN on each of the I,Q channels Imaginary Real

  10. Background noise Imaginary Real

  11. Rayleigh and Rician Probability Distribution Functions

  12. High SNR

  13. Dependence on SNR

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