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38 results on '"Shang, Desheng"'

3. Comparisons of Accelerated Continuous and Intermittent Theta Burst Stimulation for Treatment-Resistant Depression and Suicidal Ideation

Author

Zhao, Haoyang, Jiang, Chaonan, Zhao, Miaomiao, Ye, Yang, Yu, Liang, Li, Ying, Luan, Honglin, Zhang, Shiyi, Xu, Pengfeng, Chen, Xuanqiang, Pan, Fen, Shang, Desheng, Hu, Xiaohan, Jin, Kangyu, Chen, Jingkai, Mou, Tingting, Hu, Shaohua, Fitzgibbon, Bernadette M., Fitzgerald, Paul B., Cash, Robin F.H., Che, Xianwei, and Huang, Manli

Published
2024
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4. SD-CNN: a Shallow-Deep CNN for Improved Breast Cancer Diagnosis

Author

Gao, Fei, Wu, Teresa, Li, Jing, Zheng, Bin, Ruan, Lingxiang, Shang, Desheng, and Patel, Bhavika

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Breast cancer is the second leading cause of cancer death among women worldwide. Nevertheless, it is also one of the most treatable malignances if detected early. Screening for breast cancer with digital mammography (DM) has been widely used. However it demonstrates limited sensitivity for women with dense breasts. An emerging technology in the field is contrast-enhanced digital mammography (CEDM), which includes a low energy (LE) image similar to DM, and a recombined image leveraging tumor neoangiogenesis similar to breast magnetic resonance imaging (MRI). CEDM has shown better diagnostic accuracy than DM. While promising, CEDM is not yet widely available across medical centers. In this research, we propose a Shallow-Deep Convolutional Neural Network (SD-CNN) where a shallow CNN is developed to derive "virtual" recombined images from LE images, and a deep CNN is employed to extract novel features from LE, recombined or "virtual" recombined images for ensemble models to classify the cases as benign vs. cancer. To evaluate the validity of our approach, we first develop a deep-CNN using 49 CEDM cases collected from Mayo Clinic to prove the contributions from recombined images for improved breast cancer diagnosis (0.86 in accuracy using LE imaging vs. 0.90 in accuracy using both LE and recombined imaging). We then develop a shallow-CNN using the same 49 CEDM cases to learn the nonlinear mapping from LE to recombined images. Next, we use 69 DM cases collected from the hospital located at Zhejiang University, China to generate "virtual" recombined images. Using DM alone provides 0.91 in accuracy, whereas SD-CNN improves the diagnostic accuracy to 0.95.

Published
2018
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7. Comparisons of Accelerated Continuous and Intermittent Theta Burst Stimulation for Treatment-Resistant Depression and Suicidal Ideation

Author

Zhao, Haoyang, primary, Jiang, Chaonan, additional, Zhao, Miaomiao, additional, Ye, Yang, additional, Yu, Liang, additional, Li, Ying, additional, Luan, Honglin, additional, Zhang, Shiyi, additional, Xu, Pengfeng, additional, Chen, Xuanqiang, additional, Pan, Fen, additional, Shang, Desheng, additional, Hu, Xiaohan, additional, Jin, Kangyu, additional, Chen, Jingkai, additional, Mou, Tingting, additional, Hu, Shaohua, additional, Fitzgibbon, Bernadette M., additional, Fitzgerald, Paul B., additional, Cash, Robin F.H., additional, Che, Xianwei, additional, and Huang, Manli, additional

Published
2023
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10. Altered Coupling Between Cerebral Blood Flow and Voxel-Mirrored Homotopic Connectivity Affects Stroke-Induced Speech Comprehension Deficits

Author

Zhang, Jie, primary, Shang, Desheng, additional, Ye, Jing, additional, Ling, Yi, additional, Zhong, Shuchang, additional, Zhang, Shuangshuang, additional, Zhang, Wei, additional, Zhang, Li, additional, Yu, Yamei, additional, He, Fangping, additional, Ye, Xiangming, additional, and Luo, Benyan, additional

Published
2022
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18. Fixel-based evidence of microstructural damage in crossing pathways improves language mapping in Post-stroke aphasia

Author

Zhang, Jie, primary, Zheng, Weihao, additional, Shang, Desheng, additional, Chen, Yating, additional, Zhong, Shuchang, additional, Ye, Jing, additional, Li, Lingling, additional, Yu, Yamei, additional, Zhang, Li, additional, Cheng, Ruidong, additional, He, Fangping, additional, Wu, Dan, additional, Ye, Xiangming, additional, and Luo, Benyan, additional

Published
2021
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22. Cerebral perfusion mediated by thalamo‐cortical functional connectivity in non‐dominant thalamus affects naming ability in aphasia.

Author

Zhang, Jie, Zhou, Zhen, Li, Lingling, Ye, Jing, Shang, Desheng, Zhong, Shuchang, Yao, Bo, Xu, Cong, Yu, Yamei, He, Fangping, Ye, Xiangming, and Luo, Benyan

Subjects
FUNCTIONAL connectivity, THALAMUS, APHASIA, CEREBRAL circulation, ISOLATION perfusion
Abstract

Naming is a commonly impaired language domain in various types of aphasia. Emerging evidence supports the cortico‐subcortical circuitry subserving naming processing, although neurovascular regulation of the non‐dominant thalamic and basal ganglia subregions underlying post‐stroke naming difficulty remains unclear. Data from 25 subacute stroke patients and 26 age‐, sex‐, and education‐matched healthy volunteers were analyzed. Region‐of‐interest‐wise functional connectivity (FC) was calculated to measure the strength of cortico‐subcortical connections. Cerebral blood flow (CBF) was determined to reflect perfusion levels. Correlation and mediation analyses were performed to identify the relationship between cortico‐subcortical connectivity, regional cerebral perfusion, and naming performance. We observed increased right‐hemispheric subcortical connectivity in patients. FC between the right posterior superior temporal sulcus (pSTS) and lateral/medial prefrontal thalamus (lPFtha/mPFtha) exhibited significantly negative correlations with total naming score. Trend‐level increased CBF in subcortical nuclei, including that in the right lPFtha, and significant negative correlations between naming and regional perfusion of the right lPFtha were observed. The relationship between CBF in the right lPFtha and naming was fully mediated by the lPFtha‐pSTS connectivity in the non‐dominant hemisphere. Our findings suggest that perfusion changes in the right thalamic subregions affect naming performance through thalamo‐cortical circuits in post‐stroke aphasia. This study highlights the neurovascular pathophysiology of the non‐dominant hemisphere and demonstrates thalamic involvement in naming after stroke. [ABSTRACT FROM AUTHOR]

Published
2022
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23. Memantine induces manic episode in a 73-year-old patient with vascular neurocognitive disorder: a case report

Author

Duan,Jinfeng, Lao,Chengming, Chen,Jinkai, Pan,Fen, Zhang,Chenlin, Xu,Weijuan, Zhou,Weihua, Hu,Jianbo, Shang,Desheng, Huang,Manli, and Xu,Yi

Subjects
Neuropsychiatric Disease and Treatment
Abstract

Jinfeng Duan,1,2 Chengming Lao,3,4 Jingkai Chen,1,2 Fen Pan,1,2 Chenlin Zhang,3 Weijuan Xu,1,2 Weihua Zhou,1,2 Jianbo Hu,1,2 Desheng Shang,1 Manli Huang,1,2 Yi Xu1,2 1Department of Psychiatry, First Affiliated Hospital, College of Medicine, Zhejiang University, The Key Laboratory of Mental Disorder’s Management of Zhejiang Province, Hangzhou, People’s Republic of China; 2Brain Research Institute of Zhejiang University, Hangzhou, People’s Republic of China; 3College of Medicine, Zhejiang University, Hangzhou, People’s Republic of China; 4Yiwu Mental Health Center, Yiwu, People’s Republic of China Abstract: Memantine, an N-methyl-D-aspartate receptor antagonist, is a well-established treatment option for moderate-to-severe cognitive impairment related to Alzheimer disease. Recently, growing evidence has indicated memantine might also be effective in treatment of affective disorders. The common drug-induced adverse events of memantine include confusion, dizziness, drowsiness, headache, insomnia, and agitation. Herein, we presented a case of a 73-year-old female patient with vascular neurocognitive disorder, who developed a manic episode after taking memantine. Keywords: memantine, depression, dementia, manic episode

Published
2018

27. Matching method of the vision image captured by the lunar rover exploring on lunar surface

Author

Zhang Wei, Wenhui Wan, Shang Desheng, Li Lichun, Xu Yinghui, Zhou Jianliang, and Sun Jun

Subjects
Matching (statistics), business.industry, Feature extraction, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Process (computing), Scale-invariant feature transform, Image (mathematics), Geography, Image texture, Robustness (computer science), Computer vision, Artificial intelligence, business, Feature detection (computer vision)
Abstract

Facing the lunar surface survey of the Lunar Exploring Engineering, the paper summarizes the environment sensing technology based on vision image. For the image matching is the most important step in the process of the lunar exploring images, the accuracy and speed of the matching method is the key problem of the lunar exploring, which play an important role in the rover auto navigating and tele-opera ting. To conquer difficult prob lem that there are significant illumination variation of the imaging, lack of image texture, and non-uniform distribution of the image texture, the huge change of the disparity for the prominent target in the scene, in the image process Engineering, the image matching method is proposed which divided the whole image into M h N regions, and each region employs the Forstner algorithm to extract featuresE by which the semi-uniform distribution features of whole image and avoiding of the features gathering is achieved. According to the semi- uniform distribution features, the Sift and Least Square Matching method are used to realize accurate image matching. Guided by the matched features of the first step, the locale plane is detected to restrict dense image registering. The matching experiments show that the method is effective to deal with the image captured by the lunar exploring rover, that has large variation of illumination and lacking of image texture. The robustness and high accuracy of the method is also proved. The method satisfied the request of the lunar surface exploring. Keywords: lunar exploring, vision image, image matching, semi-uniform distribution, feature extraction

Published
2014

28. Improving product develop process time based on process sensitivity analysis

Author

Sun Jun, Zhang Weimin, Shang Desheng, Shen Jingsong, and He Jun

Subjects
Software development process, Iterative and incremental development, business.industry, Computer science, New product development, Process capability index, Process (computing), Process control, Process performance index, Sensitivity (control systems), business, Reliability engineering
Abstract

In order to improve the performance of process completion time effectively and efficiently, a quantitative time estimate model for sequential iterative process is introduced. Methods to improve the process completion time based on the process time sensitivity to process performance parameters are presented by using a software development process as an example. The first method is choosing activities to improve according to the process sensitivities to the activity durations. The second method is choosing activities to improve according to the process sensitivities to the rework transfer possibilities. The third one is the process time improvement based on the process sensitivities to the activity durations and to the transfer possibilities simultaneously.

Published
2012

36. Aberrant Development of Cross-Frequency Multiplex Functional Connectome in First-Episode, Drug-Naive Major Depressive Disorder and Schizophrenia

Author

Li, Junle, Huang, Manli, Pan, Fen, Li, Zhen, Shen, Zhe, Jin, Kangyu, Zhao, Haoyang, Lu, Shaojia, Shang, Desheng, Xu, Yi, and Wang, Jinhui

Abstract

Background:Both major depressive disorder (MDD) and schizophrenia (SCH) are characterized by neurodevelopmental abnormalities; however, transdiagnostic and diagnosis-specific patterns of such abnormalities have rarely been examined, particularly in large-scale functional brain networks via advanced multilayer network models.Methods:Here, we collected resting-state functional magnetic resonance imaging data from 45 MDD patients, 64 SCH patients, and 48 healthy controls (HCs; 13–45 years old), and we constructed functional networks in different frequency intervals. The frequency-dependent networks were then fused by multiplex network models, followed by graph-based topological analyses.Results:We found that functional networks of the patients showed common neurodevelopmental abnormalities in the right ventromedial parietooccipital sulcus (opposite correlations with age to HCs), whereas functional networks of the MDD patients exhibited specific alterations in the left superior parietal lobule and right precentral gyrus with respect to cross-frequency interactions. These findings were quite different from those from brain networks within each frequency interval, which revealed SCH-specific neurodevelopmental abnormalities in the right superior temporal gyrus (opposite correlations with age to the other two groups) in 0.027–0.073 Hz, and SCH-specific alterations in the left superior temporal gyrus and bilateral insula in 0.073–0.198 Hz. Finally, multivariate analysis of age prediction revealed that the subcortical network lost prediction ability in both patient groups, whereas the visual network exhibited additional prediction ability in the MDD patients.Discussion and Conclusion:Altogether, these findings demonstrate transdiagnostic and diagnosis-specific neurodevelopmental abnormalities and alterations in large-scale functional brain networks between MDD and SCH, which have important implications for understanding shared and unique neural mechanisms underlying the diseases.Impact statementRecent methodological advances in network neuroscience allow integrating connectivity information from different scales or aspects through multilayer network models. Utilizing such models, we found common and specific neurodevelopmental abnormalities in multiband functional brain networks between major depressive disorder (MDD) and schizophrenia (SCH), and the abnormalities cannot be uncovered by individually analyzing brain networks within each frequency interval. These findings have important implications for understanding shared and unique neural mechanisms underlying MDD and SCH and highlight the necessity of integrating connectivity information from different frequency intervals to search for new biomarkers of the diseases.

Published
2021
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38. Quantitative investigation of solitary pulmonary nodules: dynamic contrast-enhanced MRI and histopathologic analysis.

Author

Zou Y, Zhang M, Wang Q, Shang D, Wang L, and Yu G

Subjects
Adult, Aged, Aged, 80 and over, Contrast Media, False Positive Reactions, Female, Humans, Male, Middle Aged, Radionuclide Imaging, Reproducibility of Results, Sensitivity and Specificity, Gadolinium DTPA, Image Enhancement methods, Image Interpretation, Computer-Assisted methods, Lung Neoplasms diagnostic imaging, Solitary Pulmonary Nodule pathology
Abstract

Objective: The purposes of this study were to analyze the relation between enhancement patterns on dynamic enhanced MRI and histologic microvessel patterns of solitary pulmonary nodules (SPNs) and to address the topic of false-positive findings in differentiating SPNs with dynamic MRI., Subjects and Methods: Sixty-eight patients with 68 pathologically proven SPNs (diameter

Published
2008
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