7 papers
AnyAD: Unified Any-Modality Anomaly Detection in Incomplete Multi-Sequence MRI
Changwei Wu, Yifei Chen, Yuxin Du +7
Reliable anomaly detection in brain MRI remains challenging due to the scarcity of annotated abnormal cases and the frequent absence of key imaging modalities in real clinical work…
A Large Scale Benchmark for Test Time Adaptation Methods in Medical Image Segmentation
Wenjing Yu, Shuo Jiang, Yifei Chen +9
Test time Adaptation is a promising approach for mitigating domain shift in medical image segmentation; however, current evaluations remain limited in terms of modality coverage, t…
SmaRT: Style-Modulated Robust Test-Time Adaptation for Cross-Domain Brain Tumor Segmentation in MRI
Yuanhan Wang, Yifei Chen, Shuo Jiang +7
Reliable brain tumor segmentation in MRI is indispensable for treatment planning and outcome monitoring, yet models trained on curated benchmarks often fail under domain shifts ari…
Bridging the Gap in Missing Modalities: Leveraging Knowledge Distillation and Style Matching for Brain Tumor Segmentation
Shenghao Zhu, Yifei Chen, Weihong Chen +5
Accurate and reliable brain tumor segmentation, particularly when dealing with missing modalities, remains a critical challenge in medical image analysis. Previous studies have not…
Towards Practical Alzheimer's Disease Diagnosis: A Lightweight and Interpretable Spiking Neural Model
Changwei Wu, Yifei Chen, Yuxin Du +7
Early diagnosis of Alzheimer's Disease (AD), particularly at the mild cognitive impairment stage, is essential for timely intervention. However, this process faces significant barr…
MMLNB: Multi-Modal Learning for Neuroblastoma Subtyping Classification Assisted with Textual Description Generation
Huangwei Chen, Yifei Chen, Zhenyu Yan +4
Neuroblastoma (NB), a leading cause of childhood cancer mortality, exhibits significant histopathological variability, necessitating precise subtyping for accurate prognosis and tr…