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20242026
most citedGLFC: Unified Global-Local Feature and Contrast Learning with Mamba-Enhanced UNet for Synthetic CT Generation from CBCT

2 citations · 2 across the 11 of their papers we have counts for

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eess.IV2026

SegRap2025: A Benchmark of Gross Tumor Volume and Lymph Node Clinical Target Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma

Jia Fu, Litingyu Wang, He Li +27

Accurate delineation of Gross Tumor Volume (GTV), Lymph Node Clinical Target Volume (LN CTV), and Organ-at-Risk (OAR) from Computed Tomography (CT) scans is essential for precise r…

eess.IV20252 cited

GLFC: Unified Global-Local Feature and Contrast Learning with Mamba-Enhanced UNet for Synthetic CT Generation from CBCT

Xianhao Zhou, Jianghao Wu, Huangxuan Zhao +3

Generating synthetic Computed Tomography (CT) images from Cone Beam Computed Tomography (CBCT) is desirable for improving the image quality of CBCT. Existing synthetic CT (sCT) gen…

eess.IV2024

Self-Consistent Nested Diffusion Bridge for Accelerated MRI Reconstruction

Tao Song, Yicheng Wu, Minhao Hu +6

Accelerated MRI reconstruction plays a vital role in reducing scan time while preserving image quality. While most existing methods rely on complex-valued image-space or k-space da…

eess.IV2024

Learning Modality-Aware Representations: Adaptive Group-wise Interaction Network for Multimodal MRI Synthesis

Tao Song, Yicheng Wu, Minhao Hu +6

Multimodal MR image synthesis aims to generate missing modality images by effectively fusing and mapping from a subset of available MRI modalities. Most existing methods adopt an i…

eess.IV2024

Rethinking Abdominal Organ Segmentation (RAOS) in the clinical scenario: A robustness evaluation benchmark with challenging cases

Xiangde Luo, Zihan Li, Shaoting Zhang +2

Deep learning has enabled great strides in abdominal multi-organ segmentation, even surpassing junior oncologists on common cases or organs. However, robustness on corner cases and…