Zobrazeno 1 - 10
of 1 637
pro vyhledávání: '"Dinggang, Shen"'
Publikováno v:
Communications Engineering, Vol 3, Iss 1, Pp 1-9 (2024)
Abstract Computer-aided diagnosis (CAD) has advanced medical image analysis, while large language models (LLMs) have shown potential in clinical applications. However, LLMs struggle to interpret medical images, which are critical for decision-making.
Externí odkaz:
https://doaj.org/article/9998585238824b77a43a5dc4dc7ed92f
Autor:
Kaicong Sun, Yuanwang Zhang, Jiameng Liu, Ling Yu, Yan Zhou, Fang Xie, Qihao Guo, Han Zhang, Qian Wang, Dinggang Shen
Publikováno v:
Communications Engineering, Vol 3, Iss 1, Pp 1-13 (2024)
Abstract Brain disease diagnosis using multiple imaging modalities has shown superior performance compared to using single modality, yet multi-modal data is not easily available in clinical routine due to cost or radiation risk. Here we propose a syn
Externí odkaz:
https://doaj.org/article/7d5bfb0002cd4e1abb53199ed2cf900b
Autor:
Lin Yan, Zhiying Liang, Hao Zhang, Gaosong Zhang, Weiwei Zheng, Chunguang Han, Dongsheng Yu, Hanqi Zhang, Xinxin Xie, Chang Liu, Wenxin Zhang, Hui Zheng, Jing Pei, Dinggang Shen, Xuejun Qian
Publikováno v:
Communications Medicine, Vol 4, Iss 1, Pp 1-11 (2024)
Abstract Background Though deep learning has consistently demonstrated advantages in the automatic interpretation of breast ultrasound images, its black-box nature hinders potential interactions with radiologists, posing obstacles for clinical deploy
Externí odkaz:
https://doaj.org/article/65eb8cb1c48f4cd08ce659cefda91cd8
Autor:
Qingxia Wu, Huali Li, Yan Wang, Yan Bai, Yaping Wu, Xuan Yu, Xiaodong Li, Pei Dong, Jon Xue, Dinggang Shen, Meiyun Wang
Publikováno v:
JMIR Medical Informatics, Vol 12, p e55799 (2024)
BackgroundLarge language models show promise for improving radiology workflows, but their performance on structured radiological tasks such as Reporting and Data Systems (RADS) categorization remains unexplored. ObjectiveThis study aims to evaluate
Externí odkaz:
https://doaj.org/article/e089eb15dcd54c80ab77106bddfb166f
Autor:
Zhengliang Liu, Lu Zhang, Zihao Wu, Xiaowei Yu, Chao Cao, Haixing Dai, Ninghao Liu, Jun Liu, Wei Liu, Quanzheng Li, Dinggang Shen, Xiang Li, Dajiang Zhu, Tianming Liu
Publikováno v:
Frontiers in Radiology, Vol 3 (2024)
At the dawn of of Artificial General Intelligence (AGI), the emergence of large language models such as ChatGPT show promise in revolutionizing healthcare by improving patient care, expanding medical access, and optimizing clinical processes. However
Externí odkaz:
https://doaj.org/article/4aee005b9143410bb62b7c8b88ede6dc
Being complex-valued and low in signal-to-noise ratios, magnitude-based diffusion MRI is confounded by the noise-floor that falsely elevates signal magnitude and incurs bias to the commonly used diffusion indices, such as fractional anisotropy (FA).
Externí odkaz:
http://arxiv.org/abs/2106.06992
Autor:
Jiadong Zhang, Kaicong Sun, Junwei Yang, Yan Hu, Yuning Gu, Zhiming Cui, Xiaopeng Zong, Fei Gao, Dinggang Shen
Publikováno v:
Communications Engineering, Vol 2, Iss 1, Pp 1-13 (2023)
Abstract Medical image reconstruction and synthesis are critical for imaging quality, disease diagnosis and treatment. Most of the existing generative models ignore the fact that medical imaging usually occurs in the acquisition domain, which is diff
Externí odkaz:
https://doaj.org/article/da07dc03b3c246f1978dfbf4cc0107f6
Autor:
Lei Jin, Tianyang Sun, Xi Liu, Zehong Cao, Yan Liu, Hong Chen, Yixin Ma, Jun Zhang, Yaping Zou, Yingchao Liu, Feng Shi, Dinggang Shen, Jinsong Wu
Publikováno v:
iScience, Vol 26, Iss 11, Pp 108041- (2023)
Summary: Accurate pathological classification and grading of gliomas is crucial in clinical diagnosis and treatment. The application of deep learning techniques holds promise for automated histological pathology diagnosis. In this study, we collected
Externí odkaz:
https://doaj.org/article/e6076dff1d32436684143425585f0b30
Autor:
Shuhua Ren, Yongsheng Pan, Junpeng Li, Lin Huang, Liang Cui, Donglang Jiang, Qi Huang, Yihui Guan, Qihao Guo, Dinggang Shen, Fang Xie
Publikováno v:
View, Vol 4, Iss 5, Pp n/a-n/a (2023)
Abstract Visual interpretation is considered the gold standard for amyloid scans in clinical practice. However, dichotomous classification of amyloid deposition by visual reading always results in bias due to rater experience. Therefore, there is a n
Externí odkaz:
https://doaj.org/article/3fc3363f8fe6406983aa15ad5079fea6
Autor:
Weixiong Jiang, Zhen Zhou, Guoshi Li, Weiyan Yin, Zhengwang Wu, Li Wang, Maryam Ghanbari, Gang Li, Pew-Thian Yap, Brittany R. Howell, Martin A. Styner, Essa Yacoub, Heather Hazlett, John H. Gilmore, J. Keith Smith, Kamil Ugurbil, Jed T. Elison, Han Zhang, Dinggang Shen, Weili Lin
Publikováno v:
Developmental Cognitive Neuroscience, Vol 63, Iss , Pp 101284- (2023)
Human brain undergoes rapid growth during the first few years of life. While previous research has employed graph theory to study early brain development, it has mostly focused on the topological attributes of the whole brain. However, examining regi
Externí odkaz:
https://doaj.org/article/04cfaf29e7a94f2b8ec2f8eea06f4b60