Zobrazeno 1 - 10
of 79
pro vyhledávání: '"Zhuqing Jiao"'
Publikováno v:
BioData Mining, Vol 17, Iss 1, Pp 1-23 (2024)
Abstract Alzheimer’s disease (AD) is an advanced and incurable neurodegenerative disease. Genetic variations are intrinsic etiological factors contributing to the abnormal expression of brain function and structure in AD patients. A new multimodal
Externí odkaz:
https://doaj.org/article/63e8f83050ce4c2d9d71bc41488f2f20
Publikováno v:
BMC Medical Imaging, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract Background Information complementarity can be achieved by fusing MR and CT images, and fusion images have abundant soft tissue and bone information, facilitating accurate auxiliary diagnosis and tumor target delineation. Purpose The purpose
Externí odkaz:
https://doaj.org/article/b32caf2c31944af3ba684fec326d86a2
Autor:
Lintao Song MS, Qixuan Li MS, Zhang Sai MS, Kangkang Sun MS, Wei Chen MS, Heng Zhang MS, Yibo Wang PhD, Zhuqing Jiao PhD, Xinye Ni PhD
Publikováno v:
Technology in Cancer Research & Treatment, Vol 23 (2024)
Objectives Part of the tumor localization methods in radiotherapy have poor real-time performance and may generate additional radiation. We propose a multimodal point cloud-based method for tumor localization in robotic ultrasound-guided radiotherapy
Externí odkaz:
https://doaj.org/article/cc8ecf392b71416683eef5272c6b9624
Publikováno v:
Brain and Behavior, Vol 14, Iss 6, Pp n/a-n/a (2024)
Abstract Purpose To assess changes in neurovascular coupling (NVC) by evaluating the relationship between cerebral perfusion and brain connectivity in patients with end‐stage renal disease (ESRD) undergoing hemodialysis versus in healthy control pa
Externí odkaz:
https://doaj.org/article/46c86ed9f945423ea1364c1d8a8909cb
Publikováno v:
Mathematical Biosciences and Engineering, Vol 21, Iss 3, Pp 3838-3859 (2024)
Brain functional networks derived from functional magnetic resonance imaging (fMRI) provide a promising approach to understanding cognitive processes and predicting cognitive abilities. The topological attribute parameters of global networks are take
Externí odkaz:
https://doaj.org/article/05e72011eb2640af8dc5f46a8788d5f6
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 32, Pp 3084-3094 (2024)
Brain networks/graphs have been widely recognized as powerful and efficient tools for identifying neurological disorders. In recent years, various graph neural network models have been developed to automatically extract features from brain networks.
Externí odkaz:
https://doaj.org/article/2e0f23fb5e5a4d6098f65dea80c9bf7d
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 8, Pp 14827-14845 (2023)
Effectively selecting discriminative brain regions in multi-modal neuroimages is one of the effective means to reveal the neuropathological mechanism of end-stage renal disease associated with mild cognitive impairment (ESRDaMCI). Existing multi-moda
Externí odkaz:
https://doaj.org/article/a83be81757654093a6ae91955f7fe594
Autor:
Qing Sun, Jiahui Zheng, Yutao Zhang, Xiangxiang Wu, Zhuqing Jiao, Lifang Xu, Haifeng Shi, Tongqiang Liu
Publikováno v:
Renal Failure, Vol 45, Iss 1 (2023)
AbstractObjective The brain neuromechanism in maintenance hemodialysis patients (MHD) with cognitive impairment (CI) remains unclear. The study aimed to probe the relationship between spontaneous brain activity and CI by using resting-state functiona
Externí odkaz:
https://doaj.org/article/9eb38ffdbe6246c3974c0343574628f1
Publikováno v:
Technology in Cancer Research & Treatment, Vol 22 (2023)
As an important branch of artificial intelligence and machine learning, deep learning (DL) has been widely used in various aspects of cancer auxiliary diagnosis, among which cancer prognosis is the most important part. High-accuracy cancer prognosis
Externí odkaz:
https://doaj.org/article/e10d45abf17a4670a3ecbfedbd0279e7
Publikováno v:
Technology in Cancer Research & Treatment, Vol 22 (2023)
Purpose: During ultrasound (US)-guided radiotherapy, the tissue is deformed by probe pressure, and the US image is limited by changes in tissue and organ position and geometry when the US image is aligned with computed tomography (CT) image, leading
Externí odkaz:
https://doaj.org/article/aceafc4f66df473cac1fd32bf142310e