2 citations · 4 across the 11 of their papers we have counts for
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Multimodal MRI Report Findings Supervised Brain Lesion Segmentation with Substructures
Yubin Ge, Yongsong Huang, Xiaofeng Liu
Report-supervised (RSuper) learning seeks to alleviate the need for dense tumor voxel labels with constraints derived from radiology reports (e.g., volumes, counts, sizes, location…
Dual Prompting for Diverse Count-level PET Denoising
Xiaofeng Liu, Yongsong Huang, Thibault Marin +6
The to-be-denoised positron emission tomography (PET) volumes are inherent with diverse count levels, which imposes challenges for a unified model to tackle varied cases. In this w…
Learn From Orientation Prior for Radiograph Super-Resolution: Orientation Operator Transformer
Yongsong Huang, Tomo Miyazaki, Xiaofeng Liu +3
Background and objective: High-resolution radiographic images play a pivotal role in the early diagnosis and treatment of skeletal muscle-related diseases. It is promising to enhan…
Texture and Noise Dual Adaptation for Infrared Image Super-Resolution
Yongsong Huang, Tomo Miyazaki, Xiaofeng Liu +2
Recent efforts have explored leveraging visible light images to enrich texture details in infrared (IR) super-resolution. However, this direct adaptation approach often becomes a d…