61 citations · 75 across the 11 of their papers we have counts for
6 papers · 1 filter
Large-scale Multi-sequence Pretraining for Generalizable MRI Analysis in Versatile Clinical Applications
Zelin Qiu, Xi Wang, Zhuoyao Xie +15
Multi-sequence Magnetic Resonance Imaging (MRI) offers remarkable versatility, enabling the distinct visualization of different tissue types. Nevertheless, the inherent heterogenei…
FreeTumor: Large-Scale Generative Tumor Synthesis in Computed Tomography Images for Improving Tumor Recognition
Linshan Wu, Jiaxin Zhuang, Yanning Zhou +12
Tumor is a leading cause of death worldwide, with an estimated 10 million deaths attributed to tumor-related diseases every year. AI-driven tumor recognition unlocks new possibilit…
Rethinking Annotation Granularity for Overcoming Shortcuts in Deep Learning-based Radiograph Diagnosis: A Multicenter Study
Luyang Luo, Hao Chen, Yongjie Xiao +10
Two DL models were developed using radiograph-level annotations (yes or no disease) and fine-grained lesion-level annotations (lesion bounding boxes), respectively named CheXNet an…
Deep Learning based Spectral CT Imaging
Weiwen Wu, Dianlin Hu, Chuang Niu +7
Spectral computed tomography (CT) has attracted much attention in radiation dose reduction, metal artifacts removal, tissue quantification and material discrimination. The x-ray en…
Stabilizing Deep Tomographic Reconstruction
Weiwen Wu, Dianlin Hu, Wenxiang Cong +7
Tomographic image reconstruction with deep learning is an emerging field, but a recent landmark study reveals that several deep reconstruction networks are unstable for computed to…
Deep convolution neural network model for automatic risk assessment of patients with non-metastatic nasopharyngeal carcinoma
Richard Du, Peng Cao, Lujun Han +3
Nasopharyngeal Carcinoma (NPC) is endemic cancer in the south-east Asia. With the advent of intensity-modulated radiotherapy excellent locoregional control are being achieved. Cons…