Liyilei Su

A Systematic Review for Transformer-based Long-term Series Forecasting

The emergence of deep learning has yielded noteworthy advancements in time series forecasting (TSF). Transformer architectures, in particular, have witnessed broad utilization and adoption in TSF...

Predicting Microsatellite Instability from Pathological Images Using Self-Supervised Learning Methods

ITCFN: Incomplete Triple-Modal Co-Attention Fusion Network for Mild Cognitive Impairment Conversion Prediction

A convolutional generative adversarial framework for data augmentation based on a robust optimal transport metric

UMC-FM: Uncertainty-Guided Mamba-Consistent Feature Mixing for Semi-supervised Pulmonary Vessel Segmentation

Enhancing Early Detection of Tractional Retinal Lesions in OCT via Self-Supervised Learning

SegSAM-3D: Integrating Semantic Point Prompts and Multi-Layer Feature Sampling in SAM for Medical Imaging Segmentation

Diffusion-Based Pre-Training for Label-Efficient Abdominal Multi-Organ Segmentation

Semi-supervised 3D U-Net Learning Based on Meta Pseudo Labels

Label-efficient multi-organ segmentation with a diffusion model

Accurate segmentation of multiple organs in Computed Tomography (CT) images plays a vital role in computer-aided diagnosis systems. While various supervised learning approaches have been proposed...

ITCFN: Incomplete Triple-Modal Co-Attention Fusion Network for Mild Cognitive Impairment Conversion Prediction

Alzheimer's disease (AD) is a common neurodegenerative disease among the elderly. Early prediction and timely intervention of its prodromal stage, mild cognitive impairment (MCI), can decrease the...