5 papers
Med-URWKVâ : Toward Enhanced Pretrained Pure VRWKV Models for Medical Image Segmentation
Zhenhuan Zhou, Yining Li, Yanlin Wu +3
Medical image segmentation is a fundamental task in computer-aided diagnosis and treatment. Existing approaches based on CNNs, ViTs, Mamba, and hybrid models still suffer from limi…
Deep Learning in Dental Image Analysis: A Systematic Review of Datasets, Methodologies, and Emerging Challenges
Zhenhuan Zhou, Jingbo Zhu, Yuchen Zhang +3
Efficient analysis and processing of dental images are crucial for dentists to achieve accurate diagnosis and optimal treatment planning. However, dental imaging inherently poses s…
Mixer-Informer-Based Two-Stage Transfer Learning for Long-Sequence Load Forecasting in Newly Constructed Electric Vehicle Charging Stations
Zhenhua Zhou, Bozhen Jiang, Qin Wang
The rapid rise in electric vehicle (EV) adoption demands precise charging station load forecasting, challenged by long-sequence temporal dependencies and limited data in new facili…
Cross-Frequency Collaborative Training Network and Dataset for Semi-supervised First Molar Root Canal Segmentation
Zhenhuan Zhou, Yuchen Zhang, Along He +3
Root canal (RC) treatment is a highly delicate and technically complex procedure in clinical practice, heavily influenced by the clinicians' experience and subjective judgment. Dee…
Spatial-Frequency Dual Progressive Attention Network For Medical Image Segmentation
Zhenhuan Zhou, Along He, Yanlin Wu +3
In medical images, various types of lesions often manifest significant differences in their shape and texture. Accurate medical image segmentation demands deep learning models with…