11 citations · 31 across the 15 of their papers we have counts for
8 papers · 1 filter
Active Source-free Domain Adaptation in Open-set Medical Image Segmentation via Decomposed Uncertainty and Prototype Discrepancy
Jin Yang, Yichi Zhang, Peijie Qiu +1
Deep learning (DL) methods are challenged to demonstrate robust performance across different segmentation datasets due to domain shifts, but active domain adaptation techniques enh…
FEFormer: Frequency-enhanced Vision Transformer for Generic Knowledge Extraction and Adaptive Feature Fusion in Volumetric Medical Image Segmentation
Jin Yang, Xiaobing Yu, Peijie Qiu
Accurate segmentation of organs and lesions in medical images is essential for clinical applications including diagnosis, prognosis, and treatment planning. While Vision Transforme…
QCResUNet: Joint Subject-level and Voxel-level Segmentation Quality Prediction
Peijie Qiu, Satrajit Chakrabarty, Phuc Nguyen +2
Deep learning has made significant strides in automated brain tumor segmentation from magnetic resonance imaging (MRI) scans in recent years. However, the reliability of these tool…
STA-Unet: Rethink the semantic redundant for Medical Imaging Segmentation
Vamsi Krishna Vasa, Wenhui Zhu, Xiwen Chen +3
In recent years, significant progress has been made in the medical image analysis domain using convolutional neural networks (CNNs). In particular, deep neural networks based on a…
D2-MLP: Dynamic Decomposed MLP Mixer for Medical Image Segmentation
Jin Yang, Xiaobing Yu, Peijie Qiu
Convolutional neural networks are widely used in various segmentation tasks in medical images. However, they are challenged to learn global features adaptively due to the inherent…
DGR-MIL: Exploring Diverse Global Representation in Multiple Instance Learning for Whole Slide Image Classification
Wenhui Zhu, Xiwen Chen, Peijie Qiu +3
Multiple instance learning (MIL) stands as a powerful approach in weakly supervised learning, regularly employed in histological whole slide image (WSI) classification for detectin…
SelfReg-UNet: Self-Regularized UNet for Medical Image Segmentation
Wenhui Zhu, Xiwen Chen, Peijie Qiu +4
Since its introduction, UNet has been leading a variety of medical image segmentation tasks. Although numerous follow-up studies have also been dedicated to improving the performan…
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-…