96 citations · 177 across the 9 of their papers we have counts for
5 papers · 1 filter
nnSAM: Plug-and-play Segment Anything Model Improves nnUNet Performance
Yunxiang Li, Bowen Jing, Zihan Li +2
Automatic segmentation of medical images is crucial in modern clinical workflows. The Segment Anything Model (SAM) has emerged as a versatile tool for image segmentation without sp…
SAMScore: A Content Structural Similarity Metric for Image Translation Evaluation
Yunxiang Li, Meixu Chen, Kai Wang +3
Image translation has wide applications, such as style transfer and modality conversion, usually aiming to generate images having both high degrees of realism and faithfulness. The…
Recurrence-free Survival Prediction under the Guidance of Automatic Gross Tumor Volume Segmentation for Head and Neck Cancers
Kai Wang, Yunxiang Li, Michael Dohopolski +4
For Head and Neck Cancers (HNC) patient management, automatic gross tumor volume (GTV) segmentation and accurate pre-treatment cancer recurrence prediction are of great importance…
LViT: Language meets Vision Transformer in Medical Image Segmentation
Zihan Li, Yunxiang Li, Qingde Li +6
Deep learning has been widely used in medical image segmentation and other aspects. However, the performance of existing medical image segmentation models has been limited by the c…
Synthetic Defocus and Look-Ahead Autofocus for Casual Videography
Xuaner Zhang, Kevin Matzen, Vivien Nguyen +3
In cinema, large camera lenses create beautiful shallow depth of field (DOF), but make focusing difficult and expensive. Accurate cinema focus usually relies on a script and a pers…