Transfer Learning in Magnetic Resonance Brain Imaging: A Systematic Review

Topic: Risk, prevention and care in population studies

We found 129 articles that applied transfer learning to MR brain imaging tasks. The most frequent applications were dementia-related classification tasks and brain tumor segmentation. The majority of articles utilized transfer learning techniques based on convolutional neural networks (CNNs). Only a few approaches utilized clearly brain MRI-specific methodology, and considered privacy issues, unseen target domains, or unlabeled data. We proposed a new categorization to group specific, widely-used approaches such as pretraining and fine-tuning CNNs; (4) There is increasing interest in transfer learning for brain MRI. Well-known public datasets have clearly contributed to the popularity of Alzheimer's diagnostics/prognostics and tumor segmentation as applications. Likewise, the availability of pretrained CNNs has promoted their utilization. Finally, the majority of the surveyed studies did not examine in detail the interpretation of their strategies after applying transfer learning, and did not compare their approach with other transfer learning approaches.

Key findings

• We found 129 articles that applied transfer learning to MR brain imaging tasks.
• The most frequent applications were dementia-related classification tasks and brain tumor segmentation.
• The majority of articles utilized transfer learning techniques based on convolutional neural networks (CNNs).
• Only a few approaches utilized clearly brain MRI-specific methodology, and considered privacy issues, unseen target domains, or unlabeled data.
• We proposed a new categorization to group specific, widely-used approaches such as pretraining and fine-tuning CNNs; (4) There is increasing interest in transfer learning for brain MRI.

Why it matters

This systematic review examined 129 articles that applied transfer learning to brain MRI tasks, most often for dementia-related classification. It is a review of machine learning methods for diagnosis, not a treatment, cure or prevention study.

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Study details

• Evidence strengthLow

Read the original

• DOI: 10.3390/jimaging7040066
• PubMed: 34460516
• Original source →
• Free full text: Journal of Imaging →

Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).

@article{valverde2021-34460516,
  author  = {Valverde, J. M. and Imani, V. and Abdollahzadeh, A. and De Feo, R. and Prakash, M. and Ciszek, R. and Tohka, J.},
  title   = {{Transfer Learning in Magnetic Resonance Brain Imaging: A Systematic Review}},
  journal = {Journal of imaging},
  year    = {2021},
  doi     = {10.3390/jimaging7040066},
  pmid    = {34460516},
  url     = {https://doi.org/10.3390/jimaging7040066}
}

Studies this one cites

Referenced by this study and also in the alzhub library, so you can read them here.

• Alzheimer's Disease Neuroimaging Initiative (ADNI): clinical characterization Neurology · 2009-12-30 · usefulness score 68/100 · Mild cognitive impairment

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