57 citations · 84 across the 18 of their papers we have counts for
10 papers · 1 filter
CNsEMD: An Expert-Annotated Multi-Field-Strength MRI Dataset and a Hyperspherical Manifold Network for Multimodal Cranial Nerve Parcellation
Lei Xie, Junxiong Huang, Guoqiang Xie +9
Cranial nerves (CNs) play essential roles in sensory, motor, and autonomic functions. Accurate CN parcellation from multimodal magnetic resonance imaging (MRI) is crucial for neuro…
Cross-Sequence Semi-Supervised Learning for Multi-Parametric MRI-Based Visual Pathway Delineation
Alou Diakite, Cheng Li, Lei Xie +5
Accurately delineating the visual pathway (VP) is crucial for understanding the human visual system and diagnosing related disorders. Exploring multi-parametric MR imaging data has…
DeepMpMRI: Tensor-decomposition Regularized Learning for Fast and High-Fidelity Multi-Parametric Microstructural MR Imaging
Wenxin Fan, Jian Cheng, Qiyuan Tian +4
Deep learning has emerged as a promising approach for learning the nonlinear mapping between diffusion-weighted MR images and tissue parameters, which enables automatic and deep un…
Enhancing Representation in Medical Vision-Language Foundation Models via Multi-Scale Information Extraction Techniques
Weijian Huang, Cheng Li, Hong-Yu Zhou +6
The development of medical vision-language foundation models has attracted significant attention in the field of medicine and healthcare due to their promising prospect in various…
AID-DTI: Accelerating High-fidelity Diffusion Tensor Imaging with Detail-Preserving Model-based Deep Learning
Wenxin Fan, Jian Cheng, Cheng Li +6
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 reconstru…
Simultaneous q-Space Sampling Optimization and Reconstruction for Fast and High-fidelity Diffusion Magnetic Resonance Imaging
Jing Yang, Jian Cheng, Cheng Li +4
Diffusion Magnetic Resonance Imaging (dMRI) plays a crucial role in the noninvasive investigation of tissue microstructural properties and structural connectivity in the \textit{in…
MLIP: Medical Language-Image Pre-training with Masked Local Representation Learning
Jiarun Liu, Hong-Yu Zhou, Cheng Li +4
Existing contrastive language-image pre-training aims to learn a joint representation by matching abundant image-text pairs. However, the number of image-text pairs in medical data…
Enhancing the vision-language foundation model with key semantic knowledge-emphasized report refinement
Weijian Huang, Cheng Li, Hao Yang +4
Recently, vision-language representation learning has made remarkable advancements in building up medical foundation models, holding immense potential for transforming the landscap…
Multimodal self-supervised learning for lesion localization
Hao Yang, Hong-Yu Zhou, Cheng Li +7
Multimodal deep learning utilizing imaging and diagnostic reports has made impressive progress in the field of medical imaging diagnostics, demonstrating a particularly strong capa…
Enhancing Representation in Radiography-Reports Foundation Model: A Granular Alignment Algorithm Using Masked Contrastive Learning
Weijian Huang, Cheng Li, Hong-Yu Zhou +6
Recently, multi-modal vision-language foundation models have gained significant attention in the medical field. While these models offer great opportunities, they still face crucia…