Transfer Learning Approaches for Brain Metastases Screenings.

Background: In this study, we examined the effectiveness of transfer learning in improving automatic segmentation of brain metastases on magnetic resonance imaging scans, with potential applications in preventive exams and remote diagnostics.

Methods: We trained three deep learning models on a public dataset from the ASNR-MICCAI Brain Metastasis Challenge 2024, fine-tuned them on a small private dataset, and compared their performance to models trained from scratch.

Results: Results showed that models using transfer learning performed better than scratch-trained models, though the improvement was not statistically substantial.