Multispectral classification techniques for terahertz pulsed imaging: an example in histopathology

Abstract

Terahertz pulsed imaging is a spectroscopic imaging modality using pulses of electromagnetic radiation (100 GHz-10 THz), and there has been recent interest in studying biomedical specimens. It is usual to display parametric images derived from the measured pulses. In this work, classification was achieved by applying multispectral clustering techniques to sets of parametric images. It was hypothesised that adequate information for clustering was carried in a small number of parametric images, providing these were weighted by complementary physical properties. Materials prepared for histopathological examination were chosen because their condition remained stable during long imaging periods and because their dehydrated state led to greater penetration of the radiation. Two specimens were examined in this pilot study, one of basal cell carcinoma and one of melanoma. Unsupervised ISODATA classification using three selected parametric terahertz pulsed images was compared qualitatively with k-means classification using the shape of the whole time series, and with conventional stained microscope slides. There was good qualitative agreement between the classifications. Classifications were consistent with the morphological appearances expected, but further work is required to determine if tumour discrimination is possible. The results have implications for the future development of the technique as the need for only a small number of features could lead to considerably reduced acquisition times.