Computational imaging applications in brain and breast cancer

Aimilia Gastounioti, Saima Rathore, Omid Haji Maghsoudi, Emily F. Conant, Despina Kontos, Spyridon Bakas

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The rapid development of advanced computational algorithms from the domain of machine learning has shown promise for application in the clinical environment to (1) assist clinicians with tedious daily tasks and allow them to focus more on complex or urgent patient management, (2) offer second reads or opinions on tasks that require specialized training, as well as (3) assist in the training and education of new clinical experts. This chapter offers an overview of the state-of-the-art deep learning applications in the field of brain and breast cancer, as well as challenges and potential methods to improve the reproducibility of deep learning algorithms in biomedical image analysis of brain and breast cancer patients. The included references should not be considered as an exhaustive literature review but as studies serving as examples for the points made in this chapter.

Original languageEnglish
Title of host publicationState of the Art in Neural Networks and their Applications
Subtitle of host publicationVolume 2
PublisherElsevier
Pages29-45
Number of pages17
ISBN (Electronic)9780128198728
ISBN (Print)9780128199121
DOIs
StatePublished - Jan 1 2022

Keywords

  • brain cancer
  • breast cancer
  • convolutional neural networks
  • Deep learning

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