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pro vyhledávání: '"Liu, Qiegen"'
Positron emission tomography (PET) is an advanced medical imaging technique that plays a crucial role in non-invasive clinical diagnosis. However, while reducing radiation exposure through low-dose PET scans is beneficial for patient safety, it often
Externí odkaz:
http://arxiv.org/abs/2407.00944
Low-dose computed tomography (LDCT) plays a vital role in clinical applications by mitigating radiation risks. Nevertheless, reducing radiation doses significantly degrades image quality. Concurrently, common deep learning methods demand extensive da
Externí odkaz:
http://arxiv.org/abs/2405.17167
Computed Tomography (CT) technology reduces radiation haz-ards to the human body through sparse sampling, but fewer sampling angles pose challenges for image reconstruction. Score-based generative models are widely used in sparse-view CT re-construct
Externí odkaz:
http://arxiv.org/abs/2405.05814
Detail features of magnetic resonance images play a cru-cial role in accurate medical diagnosis and treatment, as they capture subtle changes that pose challenges for doc-tors when performing precise judgments. However, the widely utilized naive diff
Externí odkaz:
http://arxiv.org/abs/2405.05763
Deep learning (DL) has emerged as a leading approach in accelerating MR imaging. It employs deep neural networks to extract knowledge from available datasets and then applies the trained networks to reconstruct accurate images from limited measuremen
Externí odkaz:
http://arxiv.org/abs/2402.02704
Autor:
Fan, Wenxin, Cheng, Jian, Li, Cheng, Ma, Xinrui, Yang, Jing, Zou, Juan, Wu, Ruoyou, Liu, Qiegen, Wang, Shanshan
Deep learning has shown great potential in accelerating diffusion tensor imaging (DTI). Nevertheless, existing methods tend to suffer from Rician noise and detail loss in reconstructing the DTI-derived parametric maps especially when sparsely sampled
Externí odkaz:
http://arxiv.org/abs/2401.01693
Multi-contrast magnetic resonance imaging is a significant and essential medical imaging technique.However, multi-contrast imaging has longer acquisition time and is easy to cause motion artifacts. In particular, the acquisition time for a T2-weighte
Externí odkaz:
http://arxiv.org/abs/2312.00387
Autor:
Shen, Bohui, Zhang, Wei, Liu, Xubiao, Yu, Pengfei, Jiang, Shirui, Shi, Xinchong, Zhang, Xiangsong, Zhou, Xiaoyu, Zhang, Weirui, Li, Bingxuan, Liu, Qiegen
Positron emission tomography (PET) serves as an essential tool for diagnosis of encephalopathy and brain science research. However, it suffers from the limited choice of tracers. Nowadays, with the wide application of PET imaging in neuropsychiatric
Externí odkaz:
http://arxiv.org/abs/2311.00735
Attenuation correction (AC) is essential for the generation of artifact-free and quantitatively accurate positron emission tomography (PET) images. However, AC of PET faces challenges including inter-scan motion and erroneous transformation of struct
Externí odkaz:
http://arxiv.org/abs/2310.01885
Most existing MRI reconstruction methods perform tar-geted reconstruction of the entire MR image without tak-ing specific tissue regions into consideration. This may fail to emphasize the reconstruction accuracy on im-portant tissues for diagnosis. I
Externí odkaz:
http://arxiv.org/abs/2309.00853