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Xiangyang Xu
Researcher at Huazhong University of Science and Technology
Publications - 57
Citations - 1230
Xiangyang Xu is an academic researcher from Huazhong University of Science and Technology. The author has contributed to research in topics: Segmentation & Pixel. The author has an hindex of 16, co-authored 53 publications receiving 849 citations. Previous affiliations of Xiangyang Xu include Chinese Ministry of Education.
Papers
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Journal ArticleDOI
Characteristic analysis of Otsu threshold and its applications
TL;DR: This paper proves that Otsu threshold is equal to the average of the mean levels of two classes partitioned by this threshold, and proposes an improved Otsi algorithm that constrains the search range of gray levels.
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A Two-Stage Convolutional Neural Networks for Lung Nodule Detection
Haichao Cao,Hong Liu,Enmin Song,Guangzhi Ma,Xiangyang Xu,Renchao Jin,Tengying Liu,Chih-Cheng Hung +7 more
TL;DR: A random mask is designed as the data augmentation method for training a two-stage convolutional neural networks (TSCNN) for lung nodule detection and improved the generalization ability of the false positive reduction model by means of ensemble learning.
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Dual-branch residual network for lung nodule segmentation
Haichao Cao,Hong Liu,Enmin Song,Chih-Cheng Hung,Guangzhi Ma,Xiangyang Xu,Renchao Jin,Jianguo Lu +7 more
TL;DR: In this article, a dual-branch residual network (DB-ResNet) is proposed for lung nodule segmentation in computed tomography (CT) images, which can simultaneously capture multi-view and multi-scale features.
Journal ArticleDOI
Automatic left ventricle segmentation in cardiac MRI using topological stable-state thresholding and region restricted dynamic programming.
TL;DR: Evaluation results indicate that the proposed segmentation method can improve the accuracy and robust of left ventricle segmentation on short-axis cardiac magnetic resonance images (MRI) and has great potential in improving the accuracy of computer-aided diagnosis systems in cardiovascular diseases.
Journal ArticleDOI
A cascaded dual-pathway residual network for lung nodule segmentation in CT images.
Hong Liu,Haichao Cao,Enmin Song,Guangzhi Ma,Xiangyang Xu,Renchao Jin,Jin Yong,Chih-Cheng Hung +7 more
TL;DR: A data-driven model, called the Cascaded Dual-Pathway Residual Network (CDP-ResNet) to improve the segmentation of lung nodules in the CT images, which incorporates the multi-view and multi-scale features of different nodules from CT images.