Large Foundation Model for Cancer Segmentation

Zeyu Ren*, Yudong Zhang, Shuihua Wang

*Corresponding author for this work

Research output: Contribution to journalEditorial

Abstract

Recently, large language models such as ChatGPT have made huge strides in understanding and generating human-like text and have demonstrated considerable success in natural language processing. These foundation models also perform well in computer vision. However, there is a growing need to use these technologies for specific medical tasks, especially for identifying cancer in images. This paper looks at how these foundation models, such as the segment anything model, could be used for cancer segmentation, discussing the potential benefits and challenges of applying large foundation models to help with cancer diagnoses.

Original languageEnglish
JournalTechnology in Cancer Research and Treatment
Volume23
DOIs
Publication statusPublished - 1 Jan 2024

Keywords

  • deep learning
  • foundation model
  • image segmentation
  • machine learning
  • medical image analysis
  • segment anything model (SAM)

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