9 citations · 12 across the 7 of their papers we have counts for
4 papers · 1 filter
Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning
Jin Yang, Daniel S. Marcus, Aristeidis Sotiras
Medical vision foundation models remain limited in downstream tasks, particularly volumetric medical image segmentation. While fine-tuning on labeled target-domain data improves pe…
DMC-Net: Lightweight Dynamic Multi-Scale and Multi-Resolution Convolution Network for Pancreas Segmentation in CT Images
Jin Yang, Daniel S. Marcus, Aristeidis Sotiras
Convolutional neural networks (CNNs) have shown great effectiveness in medical image segmentation. However, they may be limited in modeling large inter-subject variations in organ…
Dynamic U-Net: Adaptively Calibrate Features for Abdominal Multi-organ Segmentation
Jin Yang, Daniel S. Marcus, Aristeidis Sotiras
U-Net has been widely used for segmenting abdominal organs, achieving promising performance. However, when it is used for multi-organ segmentation, first, it may be limited in expl…
D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image Segmentation
Jin Yang, Peijie Qiu, Yichi Zhang +2
Hierarchical transformers have achieved significant success in medical image segmentation due to their large receptive field and capabilities of effectively leveraging global long-…