5 papers
Generating Progressive Images from Pathological Transitions via Diffusion Model
Zeyu Liu, Tianyi Zhang, Yufang He +3
Deep learning is widely applied in computer-aided pathological diagnosis, which alleviates the pathologist workload and provide timely clinical analysis. However, most models gener…
PuzzleTuning: Explicitly Bridge Pathological and Natural Image with Puzzles
Tianyi Zhang, Shangqing Lyu, Yanli Lei +7
Pathological image analysis is a crucial field in computer vision. Due to the annotation scarcity in the pathological field, pre-training with self-supervised learning (SSL) is wid…
CellMix: A General Instance Relationship based Method for Data Augmentation Towards Pathology Image Classification
Tianyi Zhang, Zhiling Yan, Chunhui Li +5
In pathology image analysis, obtaining and maintaining high-quality annotated samples is an extremely labor-intensive task. To overcome this challenge, mixing-based methods have em…
Shuffle Instances-based Vision Transformer for Pancreatic Cancer ROSE Image Classification
Tianyi Zhang, Youdan Feng, Yunlu Feng +6
The rapid on-site evaluation (ROSE) technique can signifi-cantly accelerate the diagnosis of pancreatic cancer by im-mediately analyzing the fast-stained cytopathological images. C…
Pancreatic Cancer ROSE Image Classification Based on Multiple Instance Learning with Shuffle Instances
Tianyi Zhang, Youdan Feng, Yunlu Feng +1
The rapid on-site evaluation (ROSE) technique can significantly ac-celerate the diagnostic workflow of pancreatic cancer by immediately analyzing the fast-stained cytopathological…