Pay Attention to the Atlas: Atlas-Guided Test-Time Adaptation Method for Robust 3D Medical Image Segmentation

arXiv:2307.00676v2 Announce Type: replace-cross
Abstract: Convolutional neural networks (CNNs) often suffer from poor performance when tested on target data that differs from the training (source) data distribution, particularly in medical imaging applications where variations in imaging protocols across different clinical sites and scanners lead to different imaging appearances. However, re-accessing source training data for unsupervised domain adaptation or labeling additional test data for model fine-tuning can be difficult due to privacy issues and high labeling costs, respectively. To solve this …

abstract applications arxiv atlas attention clinical cnns convolutional neural networks cs.cv cs.lg data distribution image imaging medical medical imaging networks neural networks performance robust segmentation test training type