A robust nonlinear tissue-component discrimination method for computational pathology.

ABSTRACT: Advances in digital pathology, specifically imaging instrumentation and data management, have allowed for the development of computational pathology tools with the potential for better, faster, and cheaper diagnosis, prognosis, and prediction of disease. Images of tissue sections frequently vary in color appearance across research laboratories and medical facilities because of differences in tissue fixation, staining protocols, and imaging instrumentation, leading to difficulty in the development of robust computational tools. To address this challenge, we propose a novel nonlinear tissue-component discrimination (NLTD) method to register automatically the color space of histopathology images and visualize individual tissue components, independent of color differences between images. Our r

SUBMITTER: Sarnecki JS 

PROVIDER: S-EPMC4808351 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature