30 citations · 43 across the 6 of their papers we have counts for
5 papers · 1 filter
Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation
Chen Chen, Kerstin Hammernik, Cheng Ouyang +3
Deep learning-based segmentation methods are vulnerable to unforeseen data distribution shifts during deployment, e.g. change of image appearances or contrasts caused by different…
TransBTS: Multimodal Brain Tumor Segmentation Using Transformer
Wenxuan Wang, Chen Chen, Meng Ding +3
Transformer, which can benefit from global (long-range) information modeling using self-attention mechanisms, has been successful in natural language processing and 2D image classi…
Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation
Cheng Ouyang, Carlo Biffi, Chen Chen +3
Few-shot semantic segmentation (FSS) has great potential for medical imaging applications. Most of the existing FSS techniques require abundant annotated semantic classes for train…
Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction
Wenjia Bai, Chen Chen, Giacomo Tarroni +6
In the recent years, convolutional neural networks have transformed the field of medical image analysis due to their capacity to learn discriminative image features for a variety o…
Multi-Task Learning for Left Atrial Segmentation on GE-MRI
Chen Chen, Wenjia Bai, Daniel Rueckert
Segmentation of the left atrium (LA) is crucial for assessing its anatomy in both pre-operative atrial fibrillation (AF) ablation planning and post-operative follow-up studies. In…