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Guanyu Yang
Researcher at Southeast University
Publications - 109
Citations - 1702
Guanyu Yang is an academic researcher from Southeast University. The author has contributed to research in topics: Computer science & Segmentation. The author has an hindex of 18, co-authored 80 publications receiving 1181 citations. Previous affiliations of Guanyu Yang include Leiden University Medical Center & Chinese Ministry of Education.
Papers
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Proceedings ArticleDOI
A Multi-Task Convolutional Neural Network for Renal Tumor Segmentation and Classification Using Multi-Phasic CT Images
Tan Pan,Huazhong Shu,Jean-Louis Coatrieux,Guanyu Yang,Chuanxia Wang,Ziwei Lu,Zhongwen Zhou,Youyong Kong,Lijun Tang,Xiaomei Zhu,Jean-Louis Dillenseger +10 more
TL;DR: A multi-task network, segmentation and classification convolutional neural network (SCNet) is presented, for preoperative assessment of renal tumor, which achieves 100% accuracy and 0.882 dice coefficient of tumor region respectively, which are better than the results of a single classification network and segmentation network.
Journal ArticleDOI
Individually adapted tube current selection and contrast medium injection protocol of coronary CT angiography based on test bolus parameters: a feasibility study.
TL;DR: It is feasible to individually adapt tube current and contrast injection protocol of CCTA based on the information of test bolus, and NoiseTB was much more closely related to NoiseCCTA when compared with BW, BMI, and BSA.
Journal ArticleDOI
Patient-Level Prediction of Multi-Classification Task at Prostate MRI Based on End-to-End Framework Learning From Diagnostic Logic of Radiologists
Lizhi Shao,Zhenyu Liu,Ye Yan,Jiangang Liu,Xiongjun Ye,Haizhui Xia,Xuehua Zhu,Yuting Zhang,Zhiying Zhang,Huiying Chen,Wei He,Cheng Liu,Min Lu,Yi Huang,Kai Sun,Xuezhi Zhou,Guanyu Yang,Jian Lu,Jie Tian +18 more
TL;DR: Zhang et al. as discussed by the authors proposed a framework (PCa-GGNet-v2) that learns from radiologists to capture signs in a separate 2D space of MRI and further associate them for the overall decision, where all steps are optimized jointly in an end-to-end trainable way.
Journal ArticleDOI
3D nonrigid medical image registration using a new information theoretic measure.
TL;DR: This work presents a novel method for the nonrigid registration of medical images based on the Arimoto entropy, a generalization of the Shannon entropy, which employed the Jensen-Arimoto divergence measure as a similarity metric to measure the statistical dependence between medical images.
Journal ArticleDOI
Left Ventricle Quantification Challenge: A Comprehensive Comparison and Evaluation of Segmentation and Regression for Mid-Ventricular Short-Axis Cardiac MR Data
Wufeng Xue,Jiahui Li,Zhiqiang Hu,Eric Kerfoot,James R. Clough,Ilkay Oksuz,Hao Xu,Vicente Grau,Fumin Guo,Matthew Ng,Xiang Li,Quanzheng Li,Lihong Liu,Jin Ma,Elias Grinias,Georgios Tziritas,Wenjun Yan,Angélica Atehortúa,Mireille Garreau,Yeonggul Jang,Alejandro Debus,Enzo Ferrante,Guanyu Yang,Tiancong Hua,Shuo Li +24 more
TL;DR: In this article, the authors conducted an unbiased evaluation and comparison of cardiac LV quantification methods that were submitted to the Left Ventricle Quantification (LVQuan) challenge, which was held in conjunction with the Statistical Atlases and Computational Modeling of the Heart (STACOM) workshop at the MICCAI 2018.