Search Results - "Zhang, Fandong"

Combining global and minutia deep features for partial high-resolution fingerprint matching by Zhang, Fandong, Xin, Shiyuan, Feng, Jufu

“…•We propose a model for mobile optical fingerprint authentication.•We propose pipelines to learn global and minutia deep features for fingerprints.•We fuse…”
Get full text

Cross-View Correspondence Reasoning Based on Bipartite Graph Convolutional Network for Mammogram Mass Detection by Liu, Yuhang, Zhang, Fandong, Zhang, Qianyi, Wang, Siwen, Wang, Yizhou, Yu, Yizhou

“…Mammogram mass detection is of great clinical significance due to its high proportion in breast cancers. The information from cross views (i.e., mediolateral…”
Get full text

AI-based strategies in breast mass ≤ 2 cm classification with mammography and tomosynthesis by Shao, Zhenzhen, Cai, Yuxin, Hao, Yujuan, Hu, Congyi, Yu, Ziling, Shen, Yue, Gao, Fei, Zhang, Fandong, Ma, Wenjuan, Zhou, Qian, Chen, Jingjing, Lu, Hong

“…To evaluate the diagnosis performance of digital mammography (DM) and digital breast tomosynthesis (DBT), DM combined DBT with AI-based strategies for breast…”
Get full text

Evaluation of the peritumoral features using radiomics and deep learning technology in non-spiculated and noncalcified masses of the breast on mammography by Guo, Fei, Li, Qiyang, Gao, Fei, Huang, Chencui, Zhang, Fandong, Xu, Jingxu, Xu, Ye, Li, Yuanzhou, Sun, Jianghong, Jiang, Li

“…To assess the significance of peritumoral features based on deep learning in classifying non-spiculated and noncalcified masses (NSNCM) on mammography. We…”
Get full text

Robust sparse representation based face recognition in an adaptive weighted spatial pyramid structure by Ma, Xiao, Zhang, Fandong, Li, Yuelong, Feng, Jufu

“…The sparse representation based classification methods has achieved significant performance in recent years. To fully exploit both the holistic and locality…”
Get full text

Performance of Deep-learning-based Artificial Intelligence on Detection of Pulmonary Nodules in Chest CT by Li, Xinling, Guo, Fangfang, Zhou, Zhen, Zhang, Fandong, Wang, Qin, Peng, Zhijun, Su, Datong, Fan, Yaguang, Wang, Ying

“…The detection of pulmonary nodules is a key step to achieving the early diagnosis and therapy of lung cancer. Deep learning based Artificial intelligence (AI)…”
Get full text

Study design of deep learning based automatic detection of cerebrovascular diseases on medical imaging: a position paper from Chinese Association of Radiologists by Zhang, Longjiang, Shi, Zhao, Chen, Min, Chen, Yingmin, Cheng, Jingliang, Fan, Li, Hong, Nan, Jia, Wenxiao, Jiang, Guihua, Ju, Shenghong, Li, Xiaogang, Li, Xiuli, Liang, Changhong, Liao, Weihua, Liu, Shiyuan, Lu, Zaiming, Ma, Lin, Ren, Ke, Rong, Pengfei, Song, Bin, Sun, Gang, Wang, Rongpin, Wen, Zhibo, Xu, Haibo, Xu, Kai, Yan, Fuhua, Yu, Yizhou, Zha, Yunfei, Zhang, Fandong, Zheng, Minwen, Zhou, Zhen, Zhu, Wenzhen, Lu, Guangming, Jin, Zhengyu

“…In recent years, with the development of artificial intelligence, especially deep learning technology, researches on automatic detection of cerebrovascular…”
Get full text

Act Like a Radiologist: Towards Reliable Multi-View Correspondence Reasoning for Mammogram Mass Detection by Liu, Yuhang, Zhang, Fandong, Chen, Chaoqi, Wang, Siwen, Wang, Yizhou, Yu, Yizhou

“…Mammogram mass detection is crucial for diagnosing and preventing the breast cancers in clinical practice. The complementary effect of multi-view mammogram…”
Get full text

Graph Convolution Based Cross-Network Multiscale Feature Fusion for Deep Vessel Segmentation by Zhao, Gangming, Liang, Kongming, Pan, Chengwei, Zhang, Fandong, Wu, Xianpeng, Hu, Xinyang, Yu, Yizhou

“…Vessel segmentation is widely used to help with vascular disease diagnosis. Vessels reconstructed using existing methods are often not sufficiently accurate to…”
Get full text

Bilateral Asymmetry Guided Counterfactual Generating Network for Mammogram Classification by Wang, Churan, Li, Jing, Zhang, Fandong, Sun, Xinwei, Dong, Hao, Yu, Yizhou, Wang, Yizhou

“…Mammogram benign or malignant classification with only image-level labels is challenging due to the absence of lesion annotations. Motivated by the symmetric…”
Get full text

Deep Dense Multi-level feature for partial high-resolution fingerprint matching by Fandong Zhang, Shiyuan Xin, Jufu Feng

“…Fingerprint sensors on mobile devices commonly have limited area, which results in partial fingerprints. Optical sensor can capture fingerprints at very high…”
Get full text

Graph Convolution Based Cross-Network Multi-Scale Feature Fusion for Deep Vessel Segmentation by Zhao, Gangming, Liang, Kongming, Pan, Chengwei, Zhang, Fandong, Wu, Xianpeng, Hu, Xinyang, Yu, Yizhou

“…Vessel segmentation is widely used to help with vascular disease diagnosis. Vessels reconstructed using existing methods are often not sufficiently accurate to…”
Get full text

Detection of Intracranial Aneurysms Using Multiphase CT Angiography with a Deep Learning Model by Wang, Jinglu, Sun, Jie, Xu, Jingxu, Lu, Shiyu, Wang, Hao, Huang, Chencui, Zhang, Fandong, Yu, Yizhou, Gao, Xiang, Wang, Ming, Wang, Yu, Ruan, Xinzhong, Pan, Yuning

“…Determine the effect of a multiphase fusion deep-learning model with automatic phase selection in detection of intracranial aneurysm (IA) from computed…”
Get full text

Compare and contrast: Detecting mammographic soft-tissue lesions with C-Net by Liu, Yuhang, Zhou, Changsheng, Zhang, Fandong, Zhang, Qianyi, Wang, Siwen, Zhou, Juan, Sheng, Fugeng, Wang, Xiaoqi, Liu, Wanhua, Wang, Yizhou, Yu, Yizhou, Lu, Guangming

“…Detecting breast soft-tissue lesions including masses, structural distortions and asymmetries is of great importance due to the high risk leading to breast…”
Get full text

Compare and contrast: Detecting mammographic soft-tissue lesions with C 2 -Net by Liu, Yuhang, Zhou, Changsheng, Zhang, Fandong, Zhang, Qianyi, Wang, Siwen, Zhou, Juan, Sheng, Fugeng, Wang, Xiaoqi, Liu, Wanhua, Wang, Yizhou, Yu, Yizhou, Lu, Guangming

“…Detecting breast soft-tissue lesions including masses, structural distortions and asymmetries is of great importance due to the high risk leading to breast…”
Get full text

Cascaded Generative and Discriminative Learning for Microcalcification Detection in Breast Mammograms by Zhang, Fandong, Luo, Ling, Sun, Xinwei, Zhou, Zhen, Li, Xiuli, Yu, Yizhou, Wang, Yizhou

“…Accurate microcalcification (μC) detection is of great importance due to its high proportion in early breast cancers. Most of the previous μC detection methods…”
Get full text

Compare and contrast: Detecting mammographic soft-tissue lesions with C2-Net by Liu, Yuhang, Zhou, Changsheng, Zhang, Fandong, Zhang, Qianyi, Wang, Siwen, Zhou, Juan, Sheng, Fugeng, Wang, Xiaoqi, Liu, Wanhua, Wang, Yizhou, Yu, Yizhou, Lu, Guangming

“…•Propose a new end-to-end deep model called C2-Net that effectively exploits multi-view information for mammogram soft-tissue lesion detection.•Propose three…”
Get full text

Learning discriminative and invariant representation for fingerprint retrieval by Song, Dehua, Li, Ruilin, Zhang, Fandong, Feng, Jufu

Get full text

Prediction of Carotid In-Stent Restenosis by Computed Tomography Angiography Carotid Plaque-Based Radiomics by Cheng, Xiaoqing, Dong, Zheng, Liu, Jia, Li, Hongxia, Zhou, Changsheng, Zhang, Fandong, Wang, Churan, Zhang, Zhiqiang, Lu, Guangming

“…In-stent restenosis (ISR) after carotid artery stenting (CAS) critically influences long-term CAS benefits and safety. The study was aimed at screening…”
Get full text

A deep-learning model for intracranial aneurysm detection on CT angiography images in China: a stepwise, multicentre, early-stage clinical validation study by Hu, Bin, Shi, Zhao, Lu, Li, Miao, Zhongchang, Wang, Hao, Zhou, Zhen, Zhang, Fandong, Wang, Rongpin, Luo, Xiao, Xu, Feng, Li, Sheng, Fang, Xiangming, Wang, Xiaodong, Yan, Ge, Lv, Fajin, Zhang, Meng, Sun, Qiu, Cui, Guangbin, Liu, Yubao, Zhang, Shu, Pan, Chengwei, Hou, Zhibo, Liang, Huiying, Pan, Yuning, Chen, Xiaoxia, Li, Xiaorong, Zhou, Fei, Schoepf, U Joseph, Varga-Szemes, Akos, Garrison Moore, W, Yu, Yizhou, Hu, Chunfeng, Zhang, Long Jiang, Hu, Bin, Shi, Zhao, Lu, Li, Miao, Zhongchang, Wang, Hao, Zhou, Zhen, Zhang, Fandong, Wang, Rongpin, Luo, Xiao, Xu, Feng, Li, Sheng, Fang, Xiangming, Wang, Xiaodong, Yan, Ge, Lv, Fajin, Zhang, Meng, Sun, Qiu, Cui, Guangbin, Liu, Yubao, Zhang, Shu, Pan, Chengwei, Hou, Zhibo, Liang, Huiying, Pan, Yuning, Chen, Xiaoxia, Li, Xiaorong, Zhou, Fei, Tan, Bin, Liu, Feidi, Chen, Feng, Gu, Hongmei, Hou, Mingli, Xu, Rui, Zuo, Rui, Tao, Shumin, Chen, Weiwei, Chai, Xue, Wang, Wulin, Dai, Yongjian, Chen, Yueqin, Zhou, Changsheng, Lu, Guang Ming, Schoepf, U.Joseph, Moore, W.Garrison, Varga-Szemes, Akos, Yu, Yizhou, Hu, Chunfeng, Zhang, Longjiang

“…Artificial intelligence (AI) models in real-world implementation are scarce. Our study aimed to develop a CT angiography (CTA)-based AI model for intracranial…”
Get full text