4 citations · 11 across the 10 of their papers we have counts for
10 papers
SSA3D: Text-Conditioned Assisted Self-Supervised Framework for Automatic Dental Abutment Design
Mianjie Zheng, Xinquan Yang, Along He +6
Abutment design is a critical step in dental implant restoration. However, manual design involves tedious measurement and fitting, and research on automating this process with AI i…
GEMeX-RMCoT: An Enhanced Med-VQA Dataset for Region-Aware Multimodal Chain-of-Thought Reasoning
Bo Liu, Xiangyu Zhao, Along He +3
Medical visual question answering aims to support clinical decision-making by enabling models to answer natural language questions based on medical images. While recent advances in…
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…
TransUKAN:Computing-Efficient Hybrid KAN-Transformer for Enhanced Medical Image Segmentation
Yanlin Wu, Tao Li, Zhihong Wang +2
U-Net is currently the most widely used architecture for medical image segmentation. Benefiting from its unique encoder-decoder architecture and skip connections, it can effectivel…
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…
FRCNet Frequency and Region Consistency for Semi-supervised Medical Image Segmentation
Along He, Tao Li, Yanlin Wu +2
Limited labeled data hinder the application of deep learning in medical domain. In clinical practice, there are sufficient unlabeled data that are not effectively used, and semi-su…
ResEnsemble-DDPM: Residual Denoising Diffusion Probabilistic Models for Ensemble Learning
Shi Zhenning, Dong Changsheng, Xie Xueshuo +3
Nowadays, denoising diffusion probabilistic models have been adapted for many image segmentation tasks. However, existing end-to-end models have already demonstrated remarkable cap…
Resfusion: Denoising Diffusion Probabilistic Models for Image Restoration Based on Prior Residual Noise
Zhenning Shi, Haoshuai Zheng, Chen Xu +6
Recently, research on denoising diffusion models has expanded its application to the field of image restoration. Traditional diffusion-based image restoration methods utilize degra…
DVPT: Dynamic Visual Prompt Tuning of Large Pre-trained Models for Medical Image Analysis
Along He, Kai Wang, Zhihong Wang +2
Limited labeled data makes it hard to train models from scratch in medical domain, and an important paradigm is pre-training and then fine-tuning. Large pre-trained models contain…
Progressive Multi-scale Consistent Network for Multi-class Fundus Lesion Segmentation
Along He, Kai Wang, Tao Li +3
Effectively integrating multi-scale information is of considerable significance for the challenging multi-class segmentation of fundus lesions because different lesions vary signif…