Name: Lucia Mocz and Philip Mocz High School: Mililani High School

1. Name: Lucia Mocz and Philip Mocz • High School: Mililani High School • Mentor: Dr. André Bachmann • Project Title: Computer-Aided Identification of Cancer from Photomicrographs by Entropy Analysis • Computer algorithms were developed for identification of cancer based on the entropy of a pixel’s neighborhood in photomicrographs of tissues obtained through biopsy or surgery. Breast, colon, and lung cancer images were analyzed. Photomicrographs originated from tumor, adjacent, and normal tissues with and without immunohistochemical reactions. A total of 576 images were examined. The information content of the photomicrographs was determined by entropy analysis. Entropy analysis was most successful in the identification of lung cancer with 71% accuracy. The accuracy in identifying breast and colon cancer was 59% and 38%, respectively. These differences in accuracy could be attributed to the different micromorphology of the three cancer types. Immunohistochemical staining had little or no effect on the results and was not required for identification. To generate a visually rich representation of the photomicrographs to aid pathologists in the identification of cancer, the images were converted to entrograms using pseudo-color transformation via sinusoidal function, phase modulation, and frequency modulation. Frequency modulated entrograms provided more detail than the original photomicrographs. In conclusion, entropy analysis is competitive with current widely used molecular-based clinical methods for identifying lung cancer. The entropy formalism provides a new set of useful tools for future research and diagnostics.