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Thyroid nodule segmentation in ultrasound images using transformer models with masked autoencoder pre-training
1
Zitationen
5
Autoren
2025
Jahr
Abstract
MAE pre-training notably reduces training time and helps themodel learn transferable features, yet overall accuracy remains constrained by limited data and nodule variability. Future work will focus on scaling up data, pre-training cross-attention layers, and exploring hybrid architectures to further boost segmentation performance.
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