Nuclear to cytoplasmic ratio & cellbody analysis of virtual biopsy images for diagnosing diseases

Traditional biopsy procedure require invasive tissue removal from a living subject, followed by time-consumin and complicated processes, so noninvasive in vivo virtual biopsy, which possesses the ability to obtain exhaustive tissue images without removing tissues, is highly desired. Some sets of in vivo virtual biopsy images provided by healthy volunteers were processed by cell segmentation approach, which is based on the watershed-based approach, Genetic algorithm and the concept of convergence index filter for automatic cell segmentation. Experimental results suggest that the proposed algorithm not only reveals high accuracy for cell segmentation but also has dramatic potential for noninvasive analysis of cell nuclear-to-cytoplasmic ratio (NC ratio), also detecting the cell body size, area or shape to locate their positions or measure useful properties using Genetic Algorithm, which is important in identifying or detecting early symptoms of diseases such as skin cancers, skin aging and oral mucosa cancer during clinical diagnosis via medical imaging analysis.