Histological imaging of a human colon polyp sample using Raman spectroscopy and self organising maps

Raman spectroscopy has previously been identified as a suitable technique for the analysis of biological samples and recent technological advancements have allowed more rapid forms of spectral mapping to be undertaken. This promising approach potentially allows more biochemical information to be obtained than would normally be possible using a standard chemical stain, however specialised techniques are required to analyse the hyperspectral datasets acquired. In this work Self Organising Maps (SOM) are applied in combination with Principal Component Analysis (PCA) to analyse a single human colon polyp sample containing varying histological features. It is demonstrated that using SOM to compress the data is robust to outlying spectral features allowing greater contrast in the image for the identification of subtle features. As a secondary outcome, the SOM method also provides an alternative visualisation approach that can be used to identify regions of histological interest within a sample.