Ultrafast and Ultrahigh-Resolution Diffuse Optical Tomography for Brain Imaging with Sensitivity Equation based Noniterative Sparse Optical Reconstruction (SENSOR)

Hyun Keol Kim, Yongyi Zhao, Ankit Raghuram, Ashok Veeraraghavan, Jacob Robinson, Andreas H. Hielscher

    Research output: Contribution to journalArticlepeer-review

    Abstract

    We introduce a novel image reconstruction method for time-resolved diffuse optical tomography (DOT) that yields submillimeter resolution in less than a second. This opens the door to high-resolution real-time DOT in imaging of the brain activity. We call this approach the sensitivity equation based noniterative sparse optical reconstruction (SENSOR) method. The high spatial resolution is achieved by implementing an asymptotic l0-norm operator that guarantees to obtain sparsest representation of reconstructed targets. The high computational speed is achieved by employing the nontruncated sensitivity equation based noniterative inverse formulation combined with reduced sensing matrix and parallel computing. We tested the new method with numerical and experimental data. The results demonstrate that the SENSOR algorithm can achieve 1 mm3 spatial-resolution optical tomographic imaging at depth of ∼60 mean free paths (MFPs) in 20∼30 milliseconds on an Intel Core i9 processor.

    Original languageEnglish (US)
    Article number107939
    JournalJournal of Quantitative Spectroscopy and Radiative Transfer
    Volume276
    DOIs
    StatePublished - Dec 2021

    Keywords

    • brain imaging
    • diffuse optical tomography
    • dimensional reduction
    • noniterative sparse image reconstruction
    • sensitivity equation
    • time domain radiative transfer

    ASJC Scopus subject areas

    • Radiation
    • Atomic and Molecular Physics, and Optics
    • Spectroscopy

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