Applications of compressive sensing in spatial frequency domain imaging.

Ben O L Mellors,Christopher R Howle,Abigail M Spear,Hamid Dehghani,Alexander Bentley

doi:10.1117/1.jbo.25.11.112904

Abstract

.Significance: Spatial frequency domain imaging (SFDI) is an imaging modality that projects spatially modulated light patterns to determine optical property maps for absorption and reduced scattering of biological tissue via a pixel-by-pixel data acquisition and analysis procedure. Compressive sensing (CS) is a signal processing methodology which aims to reproduce the original signal with a reduced number of measurements, addressing the pixel-wise nature of SFDI. These methodologies have been combined for complex heterogenous data in both the image detection and data analysis stage in a compressive sensing SFDI (cs-SFDI) approach, showing reduction in both the data acquisition and overall computational time.Aim: Application of CS in SFDI data acquisition and image reconstruction significantly improves data collection and image recovery time without loss of quantitative accuracy.Approach: cs-SFDI has been applied to an increased heterogenic sample from the AppSFDI data set (back of the hand), highlighting the increased number of CS measurements required as compared to simple phantoms to accurately obtain optical property maps. A novel application of CS to the parameter recovery stage of image analysis has also been developed and validated.Results: Dimensionality reduction has been demonstrated using the increased heterogenic sample at both the acquisition and analysis stages. A data reduction of 30% for the cs-SFDI and up to 80% for the parameter recover was achieved as compared to traditional SFDI, while maintaining an error of for the recovered optical property maps.Conclusion: The application of data reduction through CS demonstrates additional capabilities for multi- and hyperspectral SFDI, providing advanced optical and physiological property maps.

Highlights

Spatial frequency domain imaging (SFDI) is a form of diffuse optical imaging, traditionally performed within the visible/near-infrared (VIS/NIR) range.[1]
The compressive sensing SFDI (cs-SFDI) process was performed upon the AppSFDI data for 820-3686 patterns, representing up to a 90% reduction in measurements required, at 10% reduction intervals
While this demonstrates a further application of Compressive sensing (CS) to SFDI, and a novel methodology for obtaining the optical property maps, as with the cs-SFDI technique, the heterogeneity of the sample is low compared to research and clinical applications of SFDI

Summary

Introduction

Spatial frequency domain imaging (SFDI) is a form of diffuse optical imaging, traditionally performed within the visible/near-infrared (VIS/NIR) range.[1]. The wavelengths used by the system can be optimized for the samples of interest, and have been extended beyond the VIS/NIR range.[3,4] Multiple wavelengths can be imaged simultaneously using more than one monochrome camera or with temporally modulated illumination, both reducing the imaging time required.[2,5] While these methods still use the two spatial frequencies and three phases, the single snapshot of optical property (SSOP) method requires only one illumination image at a non-zero spatial frequency, by performing the initial image analysis directly in the frequency domain, increasing the acquisition rate by six-fold as a form of data acquisition improvement.[6]

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