130 citations · 306 across the 28 of their papers we have counts for
10 papers · 1 filter
Adversarial Medical Image with Hierarchical Feature Hiding
Qingsong Yao, Zecheng He, Yuexiang Li +4
Deep learning based methods for medical images can be easily compromised by adversarial examples (AEs), posing a great security flaw in clinical decision-making. It has been discov…
Bi-Modality Medical Image Synthesis Using Semi-Supervised Sequential Generative Adversarial Networks
Xin Yang, Yi Lin, Zhiwei Wang +2
In this paper, we propose a bi-modality medical image synthesis approach based on sequential generative adversarial network (GAN) and semi-supervised learning. Our approach consist…
PromptMRG: Diagnosis-Driven Prompts for Medical Report Generation
Haibo Jin, Haoxuan Che, Yi Lin +1
Automatic medical report generation (MRG) is of great research value as it has the potential to relieve radiologists from the heavy burden of report writing. Despite recent advance…
Rethinking Boundary Detection in Deep Learning Models for Medical Image Segmentation
Yi Lin, Dong Zhang, Xiao Fang +3
Medical image segmentation is a fundamental task in the community of medical image analysis. In this paper, a novel network architecture, referred to as Convolution, Transformer, a…
Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directions
Luyang Luo, Xi Wang, Yi Lin +7
Breast cancer has reached the highest incidence rate worldwide among all malignancies since 2020. Breast imaging plays a significant role in early diagnosis and intervention to imp…
Exploring Visual Prompts for Whole Slide Image Classification with Multiple Instance Learning
Yi Lin, Zhongchen Zhao, Zhengjie ZHU +3
Multiple instance learning (MIL) has emerged as a popular method for classifying histopathology whole slide images (WSIs). However, existing approaches typically rely on pre-traine…
Few Shot Medical Image Segmentation with Cross Attention Transformer
Yi Lin, Yufan Chen, Kwang-Ting Cheng +1
Medical image segmentation has made significant progress in recent years. Deep learning-based methods are recognized as data-hungry techniques, requiring large amounts of data with…
Boosting Convolution with Efficient MLP-Permutation for Volumetric Medical Image Segmentation
Yi Lin, Xiao Fang, Dong Zhang +2
Recently, the advent of vision Transformer (ViT) has brought substantial advancements in 3D dataset benchmarks, particularly in 3D volumetric medical image segmentation (Vol-MedSeg…
Label-Efficient Deep Learning in Medical Image Analysis: Challenges and Future Directions
Cheng Jin, Zhengrui Guo, Yi Lin +2
Deep learning has significantly advanced medical imaging analysis (MIA), achieving state-of-the-art performance across diverse clinical tasks. However, its success largely depends…
TAKT: Target-Aware Knowledge Transfer for Whole Slide Image Classification
Conghao Xiong, Yi Lin, Hao Chen +5
Transferring knowledge from a source domain to a target domain can be crucial for whole slide image classification, since the number of samples in a dataset is often limited due to…