11 citations · 29 across the 6 of their papers we have counts for
6 papers
Swin MAE: Masked Autoencoders for Small Datasets
Zi'an Xu, Yin Dai, Fayu Liu +5
The development of deep learning models in medical image analysis is majorly limited by the lack of large-sized and well-annotated datasets. Unsupervised learning does not require…
An Anatomy-aware Framework for Automatic Segmentation of Parotid Tumor from Multimodal MRI
Yifan Gao, Yin Dai, Fayu Liu +2
Magnetic Resonance Imaging (MRI) plays an important role in diagnosing the parotid tumor, where accurate segmentation of tumors is highly desired for determining appropriate treatm…
Segmentation of Parotid Gland Tumors Using Multimodal MRI and Contrastive Learning
Zi'an Xu, Yin Dai, Fayu Liu +3
Parotid gland tumor is a common type of head and neck tumor. Segmentation of the parotid glands and tumors by MR images is important for the treatment of parotid gland tumors. Howe…
Parotid Gland MRI Segmentation Based on Swin-Unet and Multimodal Images
Zi'an Xu, Yin Dai, Fayu Liu +4
Background and objective: Parotid gland tumors account for approximately 2% to 10% of head and neck tumors. Preoperative tumor localization, differential diagnosis, and subsequent…
Mutual Attention-based Hybrid Dimensional Network for Multimodal Imaging Computer-aided Diagnosis
Yin Dai, Yifan Gao, Fayu Liu +1
Recent works on Multimodal 3D Computer-aided diagnosis have demonstrated that obtaining a competitive automatic diagnosis model when a 3D convolution neural network (CNN) brings mo…
TransMed: Transformers Advance Multi-modal Medical Image Classification
Yin Dai, Yifan Gao
Over the past decade, convolutional neural networks (CNN) have shown very competitive performance in medical image analysis tasks, such as disease classification, tumor segmentatio…