Zobrazeno 1 - 10
of 112
pro vyhledávání: '"Qin, Binjie"'
Video decomposition is very important to extract moving foreground objects from complex backgrounds in computer vision, machine learning, and medical imaging, e.g., extracting moving contrast-filled vessels from the complex and noisy backgrounds of X
Externí odkaz:
http://arxiv.org/abs/2204.10105
Autor:
Qin, Binjie, Mao, Haohao, Liu, Yiming, Zhao, Jun, Lv, Yisong, Zhu, Yueqi, Ding, Song, Chen, Xu
Although robust PCA has been increasingly adopted to extract vessels from X-ray coronary angiography (XCA) images, challenging problems such as inefficient vessel-sparsity modelling, noisy and dynamic background artefacts, and high computational cost
Externí odkaz:
http://arxiv.org/abs/2204.08466
Autor:
Dong, Zhixia, Zhao, Xiangyun, Zheng, Hangbin, Zheng, HanYao, Chen, Dafan, Cao, Jia, Xiao, Zili, Sun, Yunwei, Zhuang, Qian, Wu, Shan, Xia, Jie, Ning, Min, Qin, Binjie, Zhou, Hui, Bao, Jinsong, Wan, Xinjian
Publikováno v:
In eClinicalMedicine July 2024 73
Publikováno v:
Neural Networks, 2020
This paper develops a novel encoder-decoder deep network architecture which exploits the several contextual frames of 2D+t sequential images in a sliding window centered at current frame to segment 2D vessel masks from the current frame. The architec
Externí odkaz:
http://arxiv.org/abs/2102.05229
Publikováno v:
IEEE Transaction on Image Processing, 2020
We propose an ultrasound speckle filtering method for not only preserving various edge features but also filtering tissue-dependent complex speckle noises in ultrasound images. The key idea is to detect these various edges using a phase congruence-ba
Externí odkaz:
http://arxiv.org/abs/1810.12538
Image textures, as a kind of local variations, provide important information for human visual system. Many image textures, especially the small-scale or stochastic textures are rich in high-frequency variations, and are difficult to be preserved. Cur
Externí odkaz:
http://arxiv.org/abs/1810.11282
Publikováno v:
In Neural Networks August 2020 128:172-187
Mutual information (MI) is a popular similarity measure for image registration, whereby good registration can be achieved by maximizing the compactness of the clusters in the joint histogram. However, MI is sensitive to the "outlier" objects that app
Externí odkaz:
http://arxiv.org/abs/1304.8052
Joint saliency map (JSM) [1] was developed to assign high joint saliency values to the corresponding saliency structures (called Joint Saliency Structures, JSSs) but zero or low joint saliency values to the outliers (or mismatches) that are introduce
Externí odkaz:
http://arxiv.org/abs/1303.0479
Autor:
Qin, Binjie, Shen, Zhuangming, Zhou, Zien, Zhou, Jiawei, Sun, Jiuai, Zhang, Hui, Hu, Mingxing, Lv, Yisong
For nonrigid image registration, matching the particular structures (or the outliers) that have missing correspondence and/or local large deformations, can be more difficult than matching the common structures with small deformations in the two image
Externí odkaz:
http://arxiv.org/abs/1302.0494