Optimization of probe geometry for diffuse optical brain imaging based on measurement density and distribution.

Area of Science:

• Biomedical optics
• Medical imaging
• Neuroimaging

Background:

• Optode geometry significantly impacts spatial resolution and detection uniformity in diffuse optical imaging (DOI) for brain activation studies.
• High-quality image reconstruction is essential for accurate localization and characterization of brain activity.

Purpose of the Study:

• To evaluate and compare the quality of reconstructed images across six different optode geometries.
• To correlate measurement density with image reconstruction quality using a laboratory tissue phantom.

Main Methods:

• Utilized a laboratory tissue phantom with an embedded object at two locations.
• Quantified overlapping measurements per pixel (measurement density) and their spatial distribution for six optode geometries.
• Assessed image quality using area ratio (AR) and contrast-to-noise ratio (CNR).

Main Results:

• Image quality metrics (AR and CNR) showed an asymptotic dependence on measurement density.
• An optimal measurement density was identified, beyond which further increases yielded diminishing returns in image quality.
• The study demonstrated a method for optimizing probe geometry to balance DOI spatial resolution and measurement density.

Conclusions:

• Probe geometry optimization is critical for enhancing spatial resolution and uniformity in DOI brain imaging.
• Achieving an optimal measurement density is key to maximizing image quality without unnecessary data acquisition.
• This research provides a practical approach for designing effective optode configurations in diffuse optical imaging.