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Quantitative Pathology Image Analysis

Pathology images contain a wealth of information at the microscopic scale, revealing information about tissue morphology and--through the use of special stains--the underlying biological function. Most pathology images, like radiology images, are currently interpreted by human observers (pathologists), but many subtle features of the disease may be overlooked. We are developing methods for computerized analysis of quantitative features within pathology images with the goal of defining "imaging phenotypes" that better characterize disease and enable precision medicine. Tasks we focus on include:

  • Image normalization and preprocessing to correct batch effects and to remove artifacts
  • Image segmentation (e.g., delineation of cells and cell nuclei)
  • Image feature extraction to identify disease phenotypes
  • Machine learning to develop models that predict disease and enable precision medicine

We have a number of publications on these topics in the Publications area