Zobrazeno 1 - 10
of 191
pro vyhledávání: '"Caixia FU"'
Publikováno v:
Cancer Imaging, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background To explore the capability of diffusion-based virtual MR elastography (vMRE) in the preoperative prediction of recurrence in hepatocellular carcinoma (HCC) and to investigate the underlying relevant histopathological characteristic
Externí odkaz:
https://doaj.org/article/3147377f470241a6b11c5386d7bbf92d
Publikováno v:
European Radiology Experimental, Vol 8, Iss 1, Pp 1-13 (2024)
Abstract Background Multi-b-value diffusion-weighted imaging (DWI) with different postprocessing models allows for evaluating hepatocellular carcinoma (HCC) proliferation, spatial heterogeneity, and feasibility of treatment strategies. We assessed sy
Externí odkaz:
https://doaj.org/article/5473d709bd874631babe64cfb8d1960c
Publikováno v:
Research in Diagnostic and Interventional Imaging, Vol 9, Iss , Pp 100038- (2024)
Objective: The objective of this study was to evaluate the clinical feasibility of deep learning reconstruction-accelerated thin-slice single-breath-hold half-Fourier single-shot turbo spin echo imaging (HASTEDL) for detecting pancreatic lesions, in
Externí odkaz:
https://doaj.org/article/3a2defabdc86426a831c877b9a5144ef
Autor:
Jia-Xiang Xin, Guang Yang, Huojun Zhang, Jianqi Li, Caixia Fu, Jiachen Wang, Rui Tong, Yan Ren, Da-Xiu Wei, Ye-Feng Yao
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-8 (2023)
Abstract Magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) have made great successes in clinical diagnosis, medical research, and neurological science. MRI provides high resolution anatomical images of tissues/organs, and MRS
Externí odkaz:
https://doaj.org/article/5c417829386a42d1aeea134ee51f4c5e
Autor:
Lei Hu, Caixia Fu, Xinyang Song, Robert Grimm, Heinrich von Busch, Thomas Benkert, Ali Kamen, Bin Lou, Henkjan Huisman, Angela Tong, Tobias Penzkofer, Moon Hyung Choi, Ivan Shabunin, David Winkel, Pengyi Xing, Dieter Szolar, Fergus Coakley, Steven Shea, Edyta Szurowska, Jing-yi Guo, Liang Li, Yue-hua Li, Jun-gong Zhao
Publikováno v:
Cancer Imaging, Vol 23, Iss 1, Pp 1-12 (2023)
Abstract Background Deep-learning-based computer-aided diagnosis (DL-CAD) systems using MRI for prostate cancer (PCa) detection have demonstrated good performance. Nevertheless, DL-CAD systems are vulnerable to high heterogeneities in DWI, which can
Externí odkaz:
https://doaj.org/article/981403f31e4c4f1e9fbc9078f839b110
Publikováno v:
Heliyon, Vol 9, Iss 7, Pp e18166- (2023)
Purpose: Evaluation of the variabilities in apparent diffusion coefficient (ADC) measurements of the spleen (ADCspleen) and the paraspinal muscles (ADCmuscle) to identify the reference organ for normalizing the ADC from the abdominal diffusion weight
Externí odkaz:
https://doaj.org/article/71a808e9da274fb7b7cd3c30087fdd73
Publikováno v:
Applied Sciences, Vol 14, Iss 2, p 575 (2024)
One of the most important applied technologies in water treatment is reverse osmosis (RO). However, membrane fouling and flux reduction pose significant challenges. The electric field, as an effective preventive measure, has received limited attentio
Externí odkaz:
https://doaj.org/article/3de6d85c564d45ffa4e447d5d16a0328
Autor:
Kun Sun, Zhicheng Jiao, Hong Zhu, Weimin Chai, Xu Yan, Caixia Fu, Jie-Zhi Cheng, Fuhua Yan, Dinggang Shen
Publikováno v:
Journal of Translational Medicine, Vol 19, Iss 1, Pp 1-10 (2021)
Abstract Background This study aimed to evaluate the utility of radiomics-based machine learning analysis with multiparametric DWI and to compare the diagnostic performance of radiomics features and mean diffusion metrics in the characterization of b
Externí odkaz:
https://doaj.org/article/81a8324a4b614d6eb6ea2be38f627b22
Autor:
Pengyi Xing, Luguang Chen, Qingsong Yang, Tao Song, Chao Ma, Robert Grimm, Caixia Fu, Tiegong Wang, Wenjia Peng, Jianping Lu
Publikováno v:
Cancer Imaging, Vol 21, Iss 1, Pp 1-11 (2021)
Abstract Background To explore the usefulness of analyzing histograms and textures of apparent diffusion coefficient (ADC) maps and T2-weighted (T2W) images to differentiate prostatic cancer (PCa) from benign prostatic hyperplasia (BPH) using histopa
Externí odkaz:
https://doaj.org/article/ac2a31eb56c84a87a873f4d7f1db5709
Autor:
Neda Gholizadeh, Peter B. Greer, John Simpson, Jonathan Goodwin, Caixia Fu, Peter Lau, Saabir Siddique, Arend Heerschap, Saadallah Ramadan
Publikováno v:
Journal of Biomedical Science, Vol 28, Iss 1, Pp 1-12 (2021)
Abstract Background Current multiparametric MRI (mp-MRI) in routine clinical practice has poor-to-moderate diagnostic performance for transition zone prostate cancer. The aim of this study was to evaluate the potential diagnostic performance of novel
Externí odkaz:
https://doaj.org/article/c17da72073e24d9dafd4acb0cc90a343