247 citations · 293 across the 14 of their papers we have counts for
19 papers
Towards Generalizable Tumor Synthesis
Qi Chen, Xiaoxi Chen, Haorui Song +4
Tumor synthesis enables the creation of artificial tumors in medical images, facilitating the training of AI models for tumor detection and segmentation. However, success in tumor…
Exploiting Structural Consistency of Chest Anatomy for Unsupervised Anomaly Detection in Radiography Images
Tiange Xiang, Yixiao Zhang, Yongyi Lu +4
Radiography imaging protocols focus on particular body regions, therefore producing images of great similarity and yielding recurrent anatomical structures across patients. Exploit…
Synthetic Data as Validation
Qixin Hu, Alan Yuille, Zongwei Zhou
This study leverages synthetic data as a validation set to reduce overfitting and ease the selection of the best model in AI development. While synthetic data have been used for au…
Boosting Dermatoscopic Lesion Segmentation via Diffusion Models with Visual and Textual Prompts
Shiyi Du, Xiaosong Wang, Yongyi Lu +5
Image synthesis approaches, e.g., generative adversarial networks, have been popular as a form of data augmentation in medical image analysis tasks. It is primarily beneficial to o…
Early Detection and Localization of Pancreatic Cancer by Label-Free Tumor Synthesis
Bowen Li, Yu-Cheng Chou, Shuwen Sun +3
Early detection and localization of pancreatic cancer can increase the 5-year survival rate for patients from 8.5% to 20%. Artificial intelligence (AI) can potentially assist radio…
Continual Learning for Abdominal Multi-Organ and Tumor Segmentation
Yixiao Zhang, Xinyi Li, Huimiao Chen +3
The ability to dynamically extend a model to new data and classes is critical for multiple organ and tumor segmentation. However, due to privacy regulations, accessing previous dat…