4 papers
Adversarial Multi-Task Learning for Liver Tumor Segmentation, Dynamic Enhancement Regression, and Classification
Xiaojiao Xiao, Qinmin Vivian Hu, Tae Hyun Kim +1
Liver tumor segmentation, dynamic enhancement regression, and classification are critical for clinical assessment and diagnosis. However, no prior work has attempted to achieve the…
T-CACE: A Time-Conditioned Autoregressive Contrast Enhancement Multi-Task Framework for Contrast-Free Liver MRI Synthesis, Segmentation, and Diagnosis
Xiaojiao Xiao, Jianfeng Zhao, Qinmin Vivian Hu +1
Magnetic resonance imaging (MRI) is a leading modality for the diagnosis of liver cancer, significantly improving the classification of the lesion and patient outcomes. However, tr…
Pyramid Hierarchical Masked Diffusion Model for Imaging Synthesis
Xiaojiao Xiao, Qinmin Vivian Hu, Guanghui Wang
Medical image synthesis plays a crucial role in clinical workflows, addressing the common issue of missing imaging modalities due to factors such as extended scan times, scan corru…
FgC2F-UDiff: Frequency-guided and Coarse-to-fine Unified Diffusion Model for Multi-modality Missing MRI Synthesis
Xiaojiao Xiao, Qinmin Vivian Hu, Guanghui Wang
Multi-modality magnetic resonance imaging (MRI) is essential for the diagnosis and treatment of brain tumors. However, missing modalities are commonly observed due to limitations i…