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Visualizing the detection area of a unilateral NMR sensor using deconvolution and back-projection
Till Überrück1, Christian Rehorn1, Robin Höhner1
1RWTH Aachen University, Institut für Technische und Makromolekulare Chemie, Worringerweg 2, 52074 Aachen, Germany.
Journal of Magnetic Resonance (San Diego, Calif. : 1997)
|October 5, 2018
Summary
Characterizing the lateral detection area of Nuclear Magnetic Resonance (NMR) sensors is now faster. New image processing techniques reduce scanning time by tenfold, improving efficiency for NMR sensor analysis.
Area of Science:
- Geophysics
- Nuclear Magnetic Resonance (NMR) Spectroscopy
- Image Processing
Background:
- Accurate interpretation of unilateral Nuclear Magnetic Resonance (NMR) sensor data requires understanding its detection volume.
- Characterizing the lateral dimension of NMR sensor detection is traditionally time-consuming, requiring small samples and extensive scanning.
- Existing methods for lateral detection area characterization are limited by sample size and long measurement durations.
Purpose of the Study:
- To develop and validate efficient mathematical procedures for characterizing the lateral detection area of unilateral NMR sensors.
- To reduce the time and complexity associated with mapping the lateral sensitivity of NMR sensors.
- To improve the practical application of NMR sensors by enabling faster and more accurate data interpretation.
Main Methods:
- Application of two image processing techniques: deconvolution algorithms and back-projection of radial field profiles.
- Utilizing larger-than-pixel-size samples to streamline the characterization process.
- Demonstration and validation using the Profile NMR-MOUSE® (PM5) instrument.
Main Results:
- Both deconvolution and back-projection methods successfully characterized the lateral detection area of the NMR sensor.
- The generated magnetic field maps showed good agreement with those obtained using traditional pixel-size test samples.
- A significant reduction in scanning time, approximately one order of magnitude, was achieved compared to conventional methods.
Conclusions:
- Mathematical image processing techniques offer a more efficient approach to characterizing the lateral detection volume of unilateral NMR sensors.
- These methods overcome the limitations of traditional techniques, enabling faster and potentially higher-resolution lateral mapping.
- The developed procedures enhance the usability and applicability of NMR sensors in various scientific and industrial fields.
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