331 citations · 1.9k across the 20 of their papers we have counts for
20 papers
3D Segmentation Guided Style-based Generative Adversarial Networks for PET Synthesis
Yang Zhou, Zhiwen Yang, Hui Zhang +3
Potential radioactive hazards in full-dose positron emission tomography (PET) imaging remain a concern, whereas the quality of low-dose images is never desirable for clinical use.…
Transformer based multiple instance learning for weakly supervised histopathology image segmentation
Ziniu Qian, Kailu Li, Maode Lai +4
Hispathological image segmentation algorithms play a critical role in computer aided diagnosis technology. The development of weakly supervised segmentation algorithm alleviates th…
Whole Brain Segmentation with Full Volume Neural Network
Yeshu Li, Jonathan Cui, Yilun Sheng +4
Whole brain segmentation is an important neuroimaging task that segments the whole brain volume into anatomically labeled regions-of-interest. Convolutional neural networks have de…
Weakly Supervised Contrastive Learning for Chest X-Ray Report Generation
An Yan, Zexue He, Xing Lu +5
Radiology report generation aims at generating descriptive text from radiology images automatically, which may present an opportunity to improve radiology reporting and interpretat…
Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
Shengyu Zhao, Jonathan Cui, Yilun Sheng +4
Numerous task-specific variants of conditional generative adversarial networks have been developed for image completion. Yet, a serious limitation remains that all existing algorit…
Microscopic fine-grained instance classification through deep attention
Mengran Fan, Tapabrata Chakrabort, Eric I-Chao Chang +2
Fine-grained classification of microscopic image data with limited samples is an open problem in computer vision and biomedical imaging. Deep learning based vision systems mostly d…