Hello World Deep Learning in Medical Imaging

Paras Lakhani, Daniel L. Gray, Carl R. Pett, Paul Nagy, George Shih

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


There is recent popularity in applying machine learning to medical imaging, notably deep learning, which has achieved state-of-the-art performance in image analysis and processing. The rapid adoption of deep learning may be attributed to the availability of machine learning frameworks and libraries to simplify their use. In this tutorial, we provide a high-level overview of how to build a deep neural network for medical image classification, and provide code that can help those new to the field begin their informatics projects.

Original languageEnglish (US)
Pages (from-to)283-289
Number of pages7
JournalJournal of Digital Imaging
Issue number3
StatePublished - Jun 1 2018


  • Artificial neural networks
  • Deep learning
  • Machine learning
  • Medical imaging

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications


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