no code implementations • 3 May 2024 • Minhui Yu, Mengqi Wu, Ling Yue, Andrea Bozoki, Mingxia Liu
Magnetic resonance imaging (MRI) and positron emission tomography (PET) are increasingly used in multimodal analysis of neurodegenerative disorders.
1 code implementation • 13 Mar 2024 • Lintao Zhang, Mengqi Wu, Lihong Wang, David C. Steffens, Guy G. Potter, Mingxia Liu
To address these issues, we propose a Joint image Denoising and motion Artifact Correction (JDAC) framework via iterative learning to handle noisy MRIs with motion artifacts, consisting of an adaptive denoising model and an anti-artifact model.
no code implementations • 10 Feb 2024 • Mengqi Wu, Lintao Zhang, Pew-Thian Yap, Hongtu Zhu, Mingxia Liu
The SST utilizes an energy-based model to comprehend the global latent distribution of a target domain and translate source latent codes toward the target domain, while SMS enables MRI synthesis with a target-specific style.
no code implementations • 19 Oct 2023 • Lijuan Zhou, Xiang Meng, Zhihuan Liu, Mengqi Wu, Zhimin Gao, Pichao Wang
This paper presents a comprehensive survey of pose-based applications utilizing deep learning, encompassing pose estimation, pose tracking, and action recognition. Pose estimation involves the determination of human joint positions from images or image sequences.