Evaluation of multispectral unmixing algorithm for HbO2 and HbR

Ravi Prakash; Juliana Benavides Lara; Kamran Avanaki

doi:10.1117/12.3003563

12 March 2024 Evaluation of multispectral unmixing algorithm for HbO₂ and HbR

Ravi Prakash, Juliana Benavides Lara, Kamran Avanaki

Proceedings Volume 12842, Photons Plus Ultrasound: Imaging and Sensing 2024; 128421C (2024) https://doi.org/10.1117/12.3003563
Event: SPIE BiOS, 2024, San Francisco, California, United States

Conference Poster

Abstract

Multispectral photoacoustic tomography (sPAT) is a technique within photoacoustic imaging that aims to separate different types of chromophores using multiwavelength measurements. In this study, we conducted sPAT simulations for circular scanning detection setup using the k-wave toolbox, focusing on two dominant absorbers in biological tissue: HbO2 and HbR. A phantom with three different concentrations (100%, 70%, and 30%) were simulated for five pairs of wavelengths (700nm,900nm; 756nm,900nm; 700nm,796nm; 756nm,796nm and 900nm,796nm, respectively). Subsequently, supervised unmixing (Spectral Fitting) and unsupervised unmixing algorithms, namely Principal Component Analysis (PCA), Independent Component Analysis (ICA), and non-negative matrix factorization (NNMF), were applied. The unmixing results were then quantitatively compared with the unmixed results to evaluate their performance in terms of recovering the concentration of the chromophores into the simulation environment. The simulation study indicated that the unsupervised based unmixing algorithm such as ICA performance was superior to others in unmixing them with two wavelengths pair.

Citation Download Citation

Ravi Prakash, Juliana Benavides Lara, and Kamran Avanaki "Evaluation of multispectral unmixing algorithm for HbO₂ and HbR", Proc. SPIE 12842, Photons Plus Ultrasound: Imaging and Sensing 2024, 128421C (12 March 2024); https://doi.org/10.1117/12.3003563

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