Zobrazeno 1 - 10
of 141
pro vyhledávání: '"Xiangchun, Liu"'
Autor:
Fan Yang, Wenjing Peng, Shuang Chen, Lijuan Wan, Rui Zhao, Xiangchun Liu, Feng Ye, Hongmei Zhang
Publikováno v:
Insights into Imaging, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Objectives Newly detected hepatic nodules during follow-up of cancer survivors receiving chemotherapy may pose a diagnostic dilemma. We investigated a series of hepatic focal nodular hyperplasia (FNH) diagnosed by either typical MRI features
Externí odkaz:
https://doaj.org/article/8cdb875029384545aca284cb8828f47a
Publikováno v:
Renal Failure, Vol 46, Iss 2 (2024)
Background and aims Diabetic kidney disease (DKD) is one of the most common complications of diabetes. It is reported that mesenchymal stem cells (MSCs) derived exosomes (MSCs-Exo) may have great clinical application potential for the treatment of DK
Externí odkaz:
https://doaj.org/article/bbaa0127c33c4c44864f8e644bb7d43f
Autor:
Zhongyi Zhang, Guixia Li, Ziqiang Wang, Feng Xia, Ning Zhao, Huibin Nie, Zezhong Ye, Joshua S. Lin, Yiyi Hui, Xiangchun Liu
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Unenhanced CT scans exhibit high specificity in detecting moderate-to-severe hepatic steatosis. Even though many CTs are scanned from health screening and various diagnostic contexts, their potential for hepatic steatosis detection has large
Externí odkaz:
https://doaj.org/article/c2792255a62448c6b08aafd6167a7726
Publikováno v:
Sensors, Vol 24, Iss 18, p 5974 (2024)
This study focuses on the problem of dense object counting. In dense scenes, variations in object scales and uneven distributions greatly hinder counting accuracy. The current methods, whether CNNs with fixed convolutional kernel sizes or Transformer
Externí odkaz:
https://doaj.org/article/ac7b56c7b3ba430583d37c793004cfb5
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-19 (2023)
Abstract Uneven lighting conditions often occur during real-life photography, such as images taken at night that may have both low-light dark areas and high-light overexposed areas. Traditional algorithms for enhancing low-light areas also increase t
Externí odkaz:
https://doaj.org/article/8a6152f24f234aab830bbf19feb920b7
Autor:
Xia Zhang, Ende Cao, Yujiao Tian, Miaomiao Zhang, Xiangchun Liu, Zhao Lei, Zhigang Zhao, Ping Cui, Qiang Ling, Ruilun Xie
Publikováno v:
Carbon Resources Conversion, Vol 5, Iss 3, Pp 193-199 (2022)
Zinc-ion hybrid supercapacitors (ZHSs), which combine the superiority of batteries and supercapacitors, will become a new development direction in the field of energy storage. The development of ZHSs with high capacity and high stability can be furth
Externí odkaz:
https://doaj.org/article/bc8b706a55e94b40947ad725550e315e
Autor:
Xiaoxu Ren, Rong Wang, Fen Liu, Quanzhen Wang, Hairong Chen, Yunfeng Hou, Lifeng Yu, Xiangchun Liu, Zhiming Jiang
Publikováno v:
Medicine; 9/27/2024, Vol. 103 Issue 39, p1-6, 6p
Publikováno v:
Journal of Translational Medicine, Vol 17, Iss 1, Pp 1-10 (2019)
Abstract Background Immunoglobulin A nephropathy (IgAN) is the leading cause of end-stage kidney disease. Previous mRNA microarray profiling studies of IgAN revealed inconsistent data. We sought to identify the aberrantly expressed genes and biologic
Externí odkaz:
https://doaj.org/article/4d9fd82a95264d7a843538a56f53f2fb
Publikováno v:
IEEE Access, Vol 7, Pp 82744-82752 (2019)
The digital image segmentation algorithm based on deep learning plays an important role in the monitoring of seabed mineral resources. The traditional segmentation algorithm has insufficient performance in the face of adhesion, and the segmentation b
Externí odkaz:
https://doaj.org/article/842e457c171a4749b98b4437638cc4ce
Autor:
Xiangchun Liu, Qi Yang, Chunyu Zhang, Jianqing Sun, Kan He, Yunming Xie, Yiying Zhang, Yu Fu, Huimao Zhang
Publikováno v:
Frontiers in Oncology, Vol 10 (2021)
ObjectiveTo develop and validate a multiregional-based magnetic resonance imaging (MRI) radiomics model and combine it with clinical data for individual preoperative prediction of lymph node (LN) metastasis in rectal cancer patients.Methods186 rectal
Externí odkaz:
https://doaj.org/article/28cd65799f3a4ec59c778f015490408a