87 citations · 141 across the 46 of their papers we have counts for
9 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…
Self-Supervised Spatial And Zero-Shot Angular Super-Resolution by Spatial-Angular Implicit Representation For Rotating-View SNR-Efficient Diffusion MRI
Yinzhe Wu, Hongyu Rui, Fanwen Wang +3
Rotating-view thick-slice acquisition is highly SNR-efficient for mesoscale diffusion MRI (dMRI) but requires numerous rotating views to satisfy Nyquist sampling, resulting in long…
Unleashing Video Language Models for Fine-grained HRCT Report Generation
Yingying Fang, Huichi Zhou, KinHei Lee +4
Generating precise diagnostic reports from High-Resolution Computed Tomography (HRCT) is critical for clinical workflow, yet it remains a formidable challenge due to the high patho…
Cyclic Self-Supervised Diffusion for Ultra Low-field to High-field MRI Synthesis
Zhenxuan Zhang, Peiyuan Jing, Zi Wang +12
Synthesizing high-quality images from low-field MRI holds significant potential. Low-field MRI is cheaper, more accessible, and safer, but suffers from low resolution and poor sign…
Automated Mapping the Pathways of Cranial Nerve II, III, V, and VII/VIII: A Multi-Parametric Multi-Stage Diffusion Tractography Atlas
Lei Xie, Jiahao Huang, Jiawei Zhang +7
Cranial nerves (CNs) play a crucial role in various essential functions of the human brain, and mapping their pathways from diffusion MRI (dMRI) provides valuable preoperative insi…
Decoupling Multi-Contrast Super-Resolution: Self-Supervised Implicit Re-Representation for Unpaired Cross-Modal Synthesis
Yinzhe Wu, Hongyu Rui, Fanwen Wang +5
Multi-contrast super-resolution (MCSR) is crucial for enhancing MRI but current deep learning methods are limited. They typically require large, paired low- and high-resolution (LR…
CT-SDM: A Sampling Diffusion Model for Sparse-View CT Reconstruction across All Sampling Rates
Liutao Yang, Jiahao Huang, Guang Yang +1
Sparse views X-ray computed tomography has emerged as a contemporary technique to mitigate radiation dose. Because of the reduced number of projection views, traditional reconstruc…
Is attention all you need in medical image analysis? A review
Giorgos Papanastasiou, Nikolaos Dikaios, Jiahao Huang +2
Medical imaging is a key component in clinical diagnosis, treatment planning and clinical trial design, accounting for almost 90% of all healthcare data. CNNs achieved performance…
Swin Deformable Attention U-Net Transformer (SDAUT) for Explainable Fast MRI
Jiahao Huang, Xiaodan Xing, Zhifan Gao +1
Fast MRI aims to reconstruct a high fidelity image from partially observed measurements. Exuberant development in fast MRI using deep learning has been witnessed recently. Meanwhil…