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Local Field Fluorescence Microscopy: Imaging Cellular Signals in Intact Hearts
Published on: March 8, 2017
Signal decomposition of transmembrane voltage-sensitive dye fluorescence using a multiresolution wavelet analysis.
Huda Asfour1, Luther M Swift, Narine Sarvazyan
1Department of Electrical and Computer Engineering, The George Washington University, Washington, DC 20052, USA. h.asfour@gmail.com
IEEE Transactions on Bio-Medical Engineering
|April 23, 2011
Summary
This study introduces a new wavelet transform method to process fluorescence signals from cardiac tissue. The technique effectively separates noise and motion artifacts, improving the analysis of electrical activation and wavefronts.
Area of Science:
- Biomedical Engineering
- Cardiovascular Physiology
- Signal Processing
Background:
- Fluorescence imaging of transmembrane voltage-sensitive dyes is crucial for studying cardiac electrical activation.
- Existing fluorescence signals often suffer from low signal-to-noise ratios (SNRs) and motion artifacts, hindering accurate analysis.
- Preprocessing is essential to overcome these limitations for reliable measurements.
Purpose of the Study:
- To introduce and validate a novel discrete wavelet transform (DWT) based processing approach for fluoresced transmembrane potentials (fTmps).
- To demonstrate the method's ability to decompose fTmp signals into distinct components: noise, action potential depolarization, and motion artifact.
- To enhance the preprocessing of fTmps for improved measurement of cardiac activation times and conduction velocities.
Main Methods:
- A discrete wavelet transform (DWT) approach was developed for processing fTmp signals.
- The coiflet4 wavelet was utilized for the decomposition and reconstruction of fTmp signals.
- The method decomposes signals into three sub-signals: noise, early depolarization (rTmp), and motion artifact (rMA).
Main Results:
- The DWT approach successfully decomposed fTmp signals contaminated with motion artifact.
- The method effectively removed baseline drift and reduced noise in the fluorescence signals.
- Wavefronts within the cardiac tissue were clearly revealed after signal processing.
- The approach streamlines fTmp preprocessing for subsequent analysis of activation and conduction.
Conclusions:
- The proposed DWT-based processing approach is a valuable tool for analyzing cardiac electrical activity using fluorescence imaging.
- It offers a promising method for studying cardiac wavefronts without requiring mechanical constraints or uncoupling agents.
- This technique is particularly useful for single-camera systems lacking ratiometric imaging capabilities.
