Zobrazeno 1 - 10
of 80
pro vyhledávání: '"He, Kelei"'
Understanding the structure of the protein-ligand complex is crucial to drug development. Existing virtual structure measurement and screening methods are dominated by docking and its derived methods combined with deep learning. However, the sampling
Externí odkaz:
http://arxiv.org/abs/2408.11356
Medical image segmentation plays a crucial role in computer-aided diagnosis. However, existing methods heavily rely on fully supervised training, which requires a large amount of labeled data with time-consuming pixel-wise annotations. Moreover, accu
Externí odkaz:
http://arxiv.org/abs/2312.16039
Cross-modality magnetic resonance (MR) image synthesis can be used to generate missing modalities from given ones. Existing (supervised learning) methods often require a large number of paired multi-modal data to train an effective synthesis model. H
Externí odkaz:
http://arxiv.org/abs/2212.01108
Publikováno v:
In Pattern Recognition February 2025 158
Autor:
He, Kelei, Gan, Chen, Li, Zhuoyuan, Rekik, Islem, Yin, Zihao, Ji, Wen, Gao, Yang, Wang, Qian, Zhang, Junfeng, Shen, Dinggang
Transformers have dominated the field of natural language processing, and recently impacted the computer vision area. In the field of medical image analysis, Transformers have also been successfully applied to full-stack clinical applications, includ
Externí odkaz:
http://arxiv.org/abs/2202.12165
Autor:
He, Kelei, Ji, Wen, Zhou, Tao, Li, Zhuoyuan, Huo, Jing, Zhang, Xin, Gao, Yang, Shen, Dinggang, Zhang, Bing, Zhang, Junfeng
Accurate segmentation of brain tumors from multi-modal Magnetic Resonance (MR) images is essential in brain tumor diagnosis and treatment. However, due to the existence of domain shifts among different modalities, the performance of networks decrease
Externí odkaz:
http://arxiv.org/abs/2105.07715
Caricature attributes provide distinctive facial features to help research in Psychology and Neuroscience. However, unlike the facial photo attribute datasets that have a quantity of annotated images, the annotations of caricature attributes are rare
Externí odkaz:
http://arxiv.org/abs/2007.09344
Autor:
He, Kelei, Lian, Chunfeng, Zhang, Bing, Zhang, Xin, Cao, Xiaohuan, Nie, Dong, Gao, Yang, Zhang, Junfeng, Shen, Dinggang
Accurate segmentation of the prostate is a key step in external beam radiation therapy treatments. In this paper, we tackle the challenging task of prostate segmentation in CT images by a two-stage network with 1) the first stage to fast localize, an
Externí odkaz:
http://arxiv.org/abs/2005.10439
Autor:
He, Kelei, Lian, Chunfeng, Adeli, Ehsan, Huo, Jing, Gao, Yang, Zhang, Bing, Zhang, Junfeng, Shen, Dinggang
Fully convolutional networks (FCNs), including UNet and VNet, are widely-used network architectures for semantic segmentation in recent studies. However, conventional FCN is typically trained by the cross-entropy or Dice loss, which only calculates t
Externí odkaz:
http://arxiv.org/abs/2005.07462
Autor:
He, Kelei, Zhao, Wei, Xie, Xingzhi, Ji, Wen, Liu, Mingxia, Tang, Zhenyu, Shi, Feng, Gao, Yang, Liu, Jun, Zhang, Junfeng, Shen, Dinggang
Understanding chest CT imaging of the coronavirus disease 2019 (COVID-19) will help detect infections early and assess the disease progression. Especially, automated severity assessment of COVID-19 in CT images plays an essential role in identifying
Externí odkaz:
http://arxiv.org/abs/2005.03832