Hyperspectral Imaging System for Tissue Classification in H&E-Stained Histological Slides

This paper presents the development of a hyperspectral imaging system for the classification of H&E-stained histological slides. The system was developed to be coupled to a conventional microscope, with software dedicated to control the instrumentation, to show a colorful live image from an RGB camera, and to acquire the hyperspectral imaging using a liquid crystal tunable filter (LCTF). Hyperspectral images of H&E-stained histological slides undergoing photodynamic therapy were classified with four machine learning algorithms to find damaged tissues (crust). The classification results were presented and show that this technique is promising to classify histological tissue regions.