184 citations · 532 across the 20 of their papers we have counts for
5 papers · 1 filter
Nucleus-aware Self-supervised Pretraining Using Unpaired Image-to-image Translation for Histopathology Images
Zhiyun Song, Penghui Du, Junpeng Yan +5
Self-supervised pretraining attempts to enhance model performance by obtaining effective features from unlabeled data, and has demonstrated its effectiveness in the field of histop…
COLosSAL: A Benchmark for Cold-start Active Learning for 3D Medical Image Segmentation
Han Liu, Hao Li, Xing Yao +6
Medical image segmentation is a critical task in medical image analysis. In recent years, deep learning based approaches have shown exceptional performance when trained on a fully-…
DRMC: A Generalist Model with Dynamic Routing for Multi-Center PET Image Synthesis
Zhiwen Yang, Yang Zhou, Hui Zhang +3
Multi-center positron emission tomography (PET) image synthesis aims at recovering low-dose PET images from multiple different centers. The generalizability of existing methods can…
Zero-shot Nuclei Detection via Visual-Language Pre-trained Models
Yongjian Wu, Yang Zhou, Jiya Saiyin +5
Large-scale visual-language pre-trained models (VLPM) have proven their excellent performance in downstream object detection for natural scenes. However, zero-shot nuclei detection…
Cyclic Learning: Bridging Image-level Labels and Nuclei Instance Segmentation
Yang Zhou, Yongjian Wu, Zihua Wang +5
Nuclei instance segmentation on histopathology images is of great clinical value for disease analysis. Generally, fully-supervised algorithms for this task require pixel-wise manua…