activity
20192026
most citedAnnotation-efficient deep learning for automatic medical image segmentation

313 citations · 347 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Early and Prediagnostic Detection of Pancreatic Cancer from Computed Tomography

Wenxuan Li, Pedro R. A. S. Bassi, Lizhou Wu +34

Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest solid malignancies, is often detected at a late and inoperable stage. Retrospective reviews of prediagnostic CT scans,…

eess.IV2022★ 1 cited

Physics-informed Deep Diffusion MRI Reconstruction with Synthetic Data: Break Training Data Bottleneck in Artificial Intelligence

Chen Qian, Haoyu Zhang, Yuncheng Gao +23

Diffusion magnetic resonance imaging (MRI) is the only imaging modality for non-invasive movement detection of in vivo water molecules, with significant clinical and research appli…

eess.IV2022★ 27 cited

Quad-Net: Quad-domain Network for CT Metal Artifact Reduction

Zilong Li, Qi Gao, Yaping Wu +5

Metal implants and other high-density objects in patients introduce severe streaking artifacts in CT images, compromising image quality and diagnostic performance. Although various…

physics.med-ph2021

High temporal resolution total-body dynamic PET imaging based on pixel-level time-activity curve correction

Zixiang Chen, Yaping Wu, Na Zhang +5

Dynamic positron emission tomography (dPET) is currently a widely used medical imaging technique for the clinical diagnosis, staging and therapy guidance of all kinds of human canc…

eess.IV2020★ 313 cited

Annotation-efficient deep learning for automatic medical image segmentation

Shanshan Wang, Cheng Li, Rongpin Wang +12

Automatic medical image segmentation plays a critical role in scientific research and medical care. Existing high-performance deep learning methods typically rely on large training…

eess.IV2019★ 6 cited

Validation of a deep learning mammography model in a population with low screening rates

Kevin Wu, Eric Wu, Yaping Wu +4

A key promise of AI applications in healthcare is in increasing access to quality medical care in under-served populations and emerging markets. However, deep learning models are o…