5 papers
Med-DANet V2: A Flexible Dynamic Architecture for Efficient Medical Volumetric Segmentation
Haoran Shen, Yifu Zhang, Wenxuan Wang +4
Recent works have shown that the computational efficiency of 3D medical image (e.g. CT and MRI) segmentation can be impressively improved by dynamic inference based on slice-wise c…
EAVL: Explicitly Align Vision and Language for Referring Image Segmentation
Yichen Yan, Xingjian He, Wenxuan Wang +2
Referring image segmentation (RIS) aims to segment an object mentioned in natural language from an image. The main challenge is text-to-pixel fine-grained correlation. In the previ…
CM-MaskSD: Cross-Modality Masked Self-Distillation for Referring Image Segmentation
Wenxuan Wang, Jing Liu, Xingjian He +5
Referring image segmentation (RIS) is a fundamental vision-language task that intends to segment a desired object from an image based on a given natural language expression. Due to…
Med-Tuning: A New Parameter-Efficient Tuning Framework for Medical Volumetric Segmentation
Jiachen Shen, Wenxuan Wang, Chen Chen +5
The "pre-training then fine-tuning (FT)" paradigm is widely adopted to boost the model performance of deep learning-based methods for medical volumetric segmentation. However, conv…
FreMIM: Fourier Transform Meets Masked Image Modeling for Medical Image Segmentation
Wenxuan Wang, Jing Wang, Chen Chen +4
The research community has witnessed the powerful potential of self-supervised Masked Image Modeling (MIM), which enables the models capable of learning visual representation from…