Machine Learning-Empowered Pathology
We developed the first fully-automated algorithm to analyze digital whole-slide histopathology images. Whole-slide histopathology images contain billions of pixels and are difficult to process. To address this challenge, we established image processing modules to identify the regions of interest and extract features describing the size, shape, and pixel intensity distribution of the cell nuclei and cytoplasm. The extracted features from lung cancer histopathology slides successfully predicted patients’ diagnoses and prognoses.
