Generative models in pathology: synthesis of diagnostic quality pathology images

Amir Safarpoor, Shivam Kalra, Hamid R. Tizhoosh

Research output: Contribution to journalComment/debatepeer-review


Within artificial intelligence and machine learning, a generative model is a powerful tool for learning any kind of data distribution. With the advent of deep learning and its success in image recognition, the field of deep generative models has clearly emerged as one of the promising fields for medical imaging. In a recent issue of The Journal of Pathology, Levine, Peng et al demonstrate the ability of generative models to synthesize high-quality pathology images. They suggested that generative models can serve as an unlimited source of images either for educating freshman pathologists or training machine learning models for diverse image analysis tasks, especially in scarce cases, while resolving patients’ privacy and confidentiality concerns.

Original languageEnglish (US)
Pages (from-to)131-132
Number of pages2
JournalJournal of Pathology
Issue number2
StatePublished - Feb 2021


  • deep learning
  • digital pathology
  • generative models

ASJC Scopus subject areas

  • Pathology and Forensic Medicine


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