A Multi-layer Perceptron Approach to Automatically Detect Tissue via NIR Multispectral Imaging

We present a novel pixel-level spectra based multi-layer perceptron(MLP) to discriminate regions of biomedical multispectral imagingdata into two categories: tissue and non-tissue. The spectra usedfor this study are 740nm, 780nm, 850nm, and 945nm as thesewavelengths are on either side of the isosbestic point for oxyhemoglobinand deoxyhemoglobin; absorbers that are common in allhealthy tissues. An MLP is trained using multispectral data from12 human subjects and 12 non-tissue objects. The MLP is testedon three multispectral challenge image sets, from which the accuracy,sensitivity, and specificity of the model yield results of 91.3%(+/-0.2%), 98.1% (+/-0.3%), and 88.5% (+/- 0.3%) respectively.