5 papers
SegMix:Shuffle-based Feedback Learning for Semantic Segmentation of Pathology Images
Zhiling Yan, Sicheng Chen, Tianyi Zhang +3
Segmentation is a critical task in computational pathology, as it identifies areas affected by disease or abnormal growth and is essential for diagnosis and treatment. However, acq…
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…
CPIA Dataset: A Comprehensive Pathological Image Analysis Dataset for Self-supervised Learning Pre-training
Nan Ying, Yanli Lei, Tianyi Zhang +6
Pathological image analysis is a crucial field in computer-aided diagnosis, where deep learning is widely applied. Transfer learning using pre-trained models initialized on natural…
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…