Automated analysis of linear array images for the detection of human papillomavirus genotypes



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Persistent infections with carcinogenic Human Papillomavirus (HPV) are a necessary cause for cervical cancer, which is the fifth most deadly cancer for women worldwide. Approximately 20 million Americans are currently infected with HPV, but only a subset will develop cervical cancer. While a negative HPV test indicates a very low risk for cervical cancer, a positive test cannot discriminate between an innocuous transient infection and a prevalent cancer. Additional information such as HPV genotype and HPV viral load is thought to improve the ability to predict which women will develop cervical cancer. The visual interpretation of hybridization-strip-based HPV genotyping results, however, is heterogeneous and poorly standardized. The need for accurate and repeatable results has led to work toward the development of a robust automated image analysis package for HPV genotyping strips.