papers

Publications (7)

eess.IV2024

Modality-Projection Universal Model for Comprehensive Full-Body Medical Imaging Segmentation

Yixin Chen, Lin Gao, Yajuan Gao +8

The integration of deep learning in medical imaging has shown great promise for enhancing diagnostic, therapeutic, and research outcomes. However, applying universal models across…

cs.AI2024

Quantitative Analysis of Molecular Transport in the Extracellular Space Using Physics-Informed Neural Network

Jiayi Xie, Hongfeng Li, Jin Cheng +5

The brain extracellular space (ECS), an irregular, extremely tortuous nanoscale space located between cells or between cells and blood vessels, is crucial for nerve cell survival.…

eess.IV2026

Efficient Image-to-Image Schrödinger Bridge for CT Field of View Extension

Zhenhao Li, Song Ni, Long Yang +6

Computed tomography (CT) is a cornerstone imaging modality for non-invasive, high-resolution visualization of internal anatomical structures. However, when the scanned object excee…

eess.IV2026

Unsupervised Deformable Image Registration with Local-Global Attention and Image Decomposition

Zhengyong Huang, Xingwen Sun, Xuting Chang +5

Deformable image registration is a critical technology in medical image analysis, with broad applications in clinical practice such as disease diagnosis, multi-modal fusion, and su…

cs.CV2026

Improving Generalization of Deep Learning for Brain Metastases Segmentation Across Institutions

Yuchen Yang, Shuangyang Zhong, Haijun Yu +4

Background: Deep learning has demonstrated significant potential for automated brain metastases (BM) segmentation; however, models trained at a singular institution often exhibit s…

cs.CV2026

Towards a general-purpose foundation model for fMRI analysis

Cheng Wang, Yu Jiang, Zhihao Peng +18

Functional MRI (fMRI) is crucial for studying brain function and diagnosing neurological disorders. However, existing analysis methods suffer from reproducibility and transferabili…

eess.IV2025

QSMnet-INR: Single-Orientation Quantitative Susceptibility Mapping via Implicit Neural Representation in k-Space

Xuan Cai, Ruo-Mi Guo, Xiao-Wen Luo +6

Quantitative Susceptibility Mapping (QSM) quantifies tissue magnetic susceptibility from magnetic-resonance phase data and plays a crucial role in brain microstructure imaging, iro…