Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology

Rohit Bhargava, Anant Madabhushi

Research output: Contribution to journalArticlepeer-review


Pathology is essential for research in disease and development, as well as for clinical decision making. For more than 100 years, pathology practice has involved analyzing images of stained, thin tissue sections by a trained human using an optical microscope. Technological advances are now driving major changes in this paradigm toward digital pathology (DP). The digital transformation of pathology goes beyond recording, archiving, and retrieving images, providing new computational tools to inform better decision making for precision medicine. First, we discuss some emerging innovations in both computational image analytics and imaging instrumentation in DP. Second, we discuss molecular contrast in pathology. Molecular DP has traditionally been an extension of pathology with molecularly specific dyes. Label-free, spectroscopic images are rapidly emerging as another important information source, and we describe the benefits and potential of this evolution. Third, we describe multimodal DP, which is enabled by computational algorithms and combines the best characteristics of structural and molecular pathology. Finally, we provide examples of application areas in telepathology, education, and precision medicine. We conclude by discussing challenges and emerging opportunities in this area.

Original languageEnglish (US)
Pages (from-to)387-412
Number of pages26
JournalAnnual Review of Biomedical Engineering
StatePublished - Jul 11 2016


  • Algorithms
  • Chemical imaging
  • Computational
  • Diagnosis
  • Digital pathology
  • FT-IR spectroscopy
  • Infrared spectroscopic imaging
  • Microenvironment
  • Outcome
  • Precision medicine
  • Prognosis
  • Stainless staining

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Biomedical Engineering


Dive into the research topics of 'Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology'. Together they form a unique fingerprint.

Cite this