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cs.CV2026
Modality-Aware and Anatomical Vector-Quantized Autoencoding for Multimodal Brain MRI
Mingjie Li, Edward Kim, Yue Zhao +2
Learning a robust Variational Autoencoder (VAE) is a fundamental step for many deep learning applications in medical image analysis, such as MRI synthesizes. Existing brain VAEs pr…
cs.CV2026
A Generative Foundation Model for Multimodal Histopathology
Jinxi Xiang, Mingjie Li, Siyu Hou +9
Accurate diagnosis and treatment of complex diseases require integrating histological, molecular, and clinical data, yet in practice these modalities are often incomplete owing to…
cs.CV2026
Redefining the Down-Sampling Scheme of U-Net for Precision Biomedical Image Segmentation
Mingjie Li, Yizheng Chen, Md Tauhidul Islam +1
U-Net architectures have been instrumental in advancing biomedical image segmentation (BIS) but often struggle with capturing long-range information. One reason is the conventional…