Yang Chen
Southeast University
Deep learningAlgorithmImage (mathematics)Iterative reconstructionNoiseArtificial intelligencePixelTomographyPattern recognitionProjection (set theory)Computer visionMathematicsComputer scienceComputed tomographyImage qualityMedicineFeature (computer vision)Convolutional neural networkSegmentationImage processing
Publications 203
#1Rongjun Ge (SEU: Southeast University)H-Index: 6
#2Yuting He (SEU: Southeast University)H-Index: 2
Last. Yinsu Zhu (Nanjing Medical University)H-Index: 7
view all 14 authors...
Abstract null null Orthogonal 2D cervical vertebra (C-vertebra) X-ray images have the advantages of high imaging efficiency, low radiation risk, easy operation and low cost for rapid primary clinical diagnoses. Especially in emergency departments, this technique is known to be significantly useful in triage for trauma patients. However, the technique can only provide overlapping anatomic information from limited projection views and is unable to visually exhibit full-view anatomy and precise ste...
#4Yang ChenH-Index: 28
#8Jian Yang (BIT: Beijing Institute of Technology)H-Index: 142
Last. Jean-Louis Coatrieux (University of Rennes)H-Index: 23
view all 11 authors...
BACKGROUND AND OBJECTIVE Aortic dissection is a severe cardiovascular pathology in which an injury of the intimal layer of the aorta allows blood flowing into the aortic wall, forcing the wall layers apart. Such situation presents a high mortality rate and requires an in-depth understanding of the 3-D morphology of the dissected aorta to plan the right treatment. An accurate automatic segmentation algorithm is therefore needed. METHOD In this paper, we propose a deep-learning-based algorithm to ...
#1Xiaoming Qi (SEU: Southeast University)
#2Yuting He (SEU: Southeast University)H-Index: 2
Last. Shuo Li (UWO: University of Western Ontario)H-Index: 41
view all 10 authors...
The accurate 3D left ventricular (LV) myocardium segmentation in short-axis (SAX) view of cardiac magnetic resonance (CMR) is challenged by the sparse spatial structure of CMR. The strategy of multi-view CMR fusion can provide fine-grained spatial structure for accurate segmentation. However, the large information misalignment & lack of dense 3D CMR as fusion target in multi-view CMR fusion, and the different spatial resolution between the fused cardiac model and the ground truth of segmentation...
#1Liang Jiang (Nanjing Medical University)H-Index: 6
#2Leilei Zhou (Nanjing Medical University)H-Index: 2
Last. Yu-Chen Chen (Nanjing Medical University)H-Index: 13
view all 10 authors...
Hemorrhagic transformation (HT) is one of the most serious complications after endovascular thrombectomy (EVT) in acute ischemic stroke (AIS) patients. The purpose of this study is to develop and validate deep-learning (DL) models based on multiparametric magnetic resonance imaging (MRI) to automatically predict HT in AIS patients. Multiparametric MRI and clinical data of AIS patients with EVT from two centers (data set 1 for training and testing: n = 338; data set 2 for validating: n = 54) were...
#1Weiya Sun (SEU: Southeast University)H-Index: 1
#2Guanyu Yang (SEU: Southeast University)H-Index: 17
Last. Huazhong Shu (SEU: Southeast University)H-Index: 36
view all 4 authors...
BACKGROUND The determination of the right x-ray angiography viewing angle is an important issue during the treatment of thoracic endovascular aortic repair (TEVAR). An inaccurate projection angle (manually determined today by the physicians according to their personal experience) may affect the placement of the stent and cause vascular occlusion or endoleak. METHODS Based on the acquisition of a computed tomography angiography (CTA) image before TEVAR, an adaptive optimization algorithm is propo...
#1Zechen Yu (SEU: Southeast University)
#2Zhongping Chen (JLU: Jilin University)
Last. Yang Chen (SEU: Southeast University)H-Index: 28
view all 6 authors...
Abstract null null Background and Purpose null As a simple and reliable systematic method to evaluate the early ischemic changes in the blood supply region of the middle cerebral artery of patients with ischemic stroke, the Alberta Stroke Program Early CT score (ASPECTS) can be used for rapid semi-quantitative evaluation of ischemic lesions, which is helpful to select potential candidates for intravenous and intra-arterial therapies, determine the thrombolytic effect and long-term prognosis. Thi...
#1Rongjun Ge (SEU: Southeast University)
#2Tengfei Shen (SEU: Southeast University)H-Index: 1
Last. Yang Chen (SEU: Southeast University)H-Index: 28
view all 9 authors...
Abstract null null Automatic detection of arrhythmia through an electrocardiogram (ECG) is of great significance for the prevention and treatment of cardiovascular diseases. In Convolutional neural network, the ECG signal is converted into multiple feature channels with equal weights through the convolution operation. Multiple feature channels can provide richer and more comprehensive information, but also contain redundant information, which will affect the diagnosis of arrhythmia, so feature c...
#1Y.B. Zhang (Sichuan University)H-Index: 16
Compressed sensing (CS) computed tomography has been proven to be important for several clinical applications, such as sparse-view computed tomography (CT), digital tomosynthesis and interior tomography. Traditional compressed sensing focuses on the design of handcrafted prior regularizers, which are usually image-dependent and time-consuming. Inspired by recently proposed deep learning-based CT reconstruction models, we extend the state-of-the-art LEARN model to a dual-domain version, dubbed LE...
#1Xiangtian Xue (SEU: Southeast University)
#2Changping Du (SEU: Southeast University)
Last. Pinzheng Zhang (SEU: Southeast University)
view all 6 authors...
Ship tracking for remote sensing video has strong background characteristics. A single network structure hardly adapts to various environmental characteristics, where the tracking in the ocean background needs to have a strong real-time performance, while it tends to pursue the accuracy of detection when there exists land interference in the scene. This paper proposes a self-selecting neural network SSNN to comprehensively utilize the superiority of deep neural network and traditional tracking a...
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