bibtext: @InProceedings{ Ola_SpeChrOmics_MICCAI2024,
                   author = { Oladokun, Ajibola S. and Malila, Bessie and Campello, Victor M. and Shey, Muki and Mutsvangwa, Tinashe E. M. },
                   title = { { SpeChrOmics: A Biomarker Characterization Framework for Medical Hyperspectral Imaging } },
                   booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2024},
                   year = {2024},
                   publisher = {Springer Nature Switzerland},
                   volume = { LNCS 15003 },
                   month = {October},
                   pages = { pending },
                }
abstract: We propose SpeChrOmics, a characterization framework for generating potential biomarkers of pathologies from hyperspectral images of body tissue. We test our model using a novel clinical application – hyperspectral imaging for the diagnosis of latent tuberculosis infection (LTBI). This is a neglected disease state predominantly prevalent in sub-Saharan Africa. Our model identified water, deoxyhemoglobin, and pheomelanin as potential chromophore biomarkers for LTBI with mean cross validation accuracy of 96%. Our framework can potentially be used for pathology characterization in other medical applications.
title: SpeChrOmics: A Biomarker Characterization Framework for Medical Hyperspectral Imaging
authors: Oladokun, Ajibola S. Malila, Bessie Campello, Victor M. Shey, Muki Mutsvangwa, Tinashe E. M.