Detection of unstained living neurospheres from phase contrast images with very large illumination variations
Live imaging of neural stem cells and progenitors is important to follow the biology of these cells. Non-invasive imaging techniques, such as phase contrast microscopy, are preferred as neural stem cells are very sensitive to photoxic damage cause by excitation of fluorescent molecules. However, large illumination variations and weak foreground/background contrast make phase contrast images challenging for image processing. In the current work, we propose a new method to segment neurospheres imaged under phase contrast microscopy by employing high dynamic range imaging and advanced level-set method. The use of high dynamic range imaging enhances the fused image by expressing cell signatures from various exposure captures. We apply advanced level-set method in cell segmentation to improve the detection rate over simple methods such as thresholding. Validation experiments in the analysis of 21 images containing over 400 cells have demonstrated accuracy improvements over existing techniques.