21 citations
- Chinese Academy of SciencesCN3 papers
- Zhengzhou UniversityCN3 papers
- Tsinghua UniversityCN2 papers
- Beihang UniversityCN1 paper
- Beijing Academy of Artificial IntelligenceCN1 paper
- Beijing Academy of Quantum Information SciencesCN1 paper
- Beijing Anzhen HospitalCN1 paper
- Capital Medical UniversityCN1 paper
- Erasmus MCNL1 paper
- IBM Research (China)CN1 paper
- Institute of Computing TechnologyCN1 paper
- Institute of High Energy PhysicsCN1 paper
7 papers
IPDiff: Diffusion-driven ORSI Salient Object Detection with Information Reconstruction and Multi-Prior Guidance
Gongyang Li, Zhen Bai, Runmin Cong +3
Existing Salient Object Detection in Optical Remote Sensing Image (ORSI-SOD) methods mainly adopt the static inference strategy, which uses fixed trained model parameters for salie…
MvKeTR: Chest CT Report Generation with Multi-View Perception and Knowledge Enhancement
Xiwei Deng, Xianchun He, Jianfeng Bao +4
CT report generation (CTRG) aims to automatically generate diagnostic reports for 3D volumes, relieving clinicians' workload and improving patient care. Despite clinical value, exi…
DSCA: A Digital Subtraction Angiography Sequence Dataset and Spatio-Temporal Model for Cerebral Artery Segmentation
Jiong Zhang, Qihang Xie, Lei Mou +6
Cerebrovascular diseases (CVDs) remain a leading cause of global disability and mortality. Digital Subtraction Angiography (DSA) sequences, recognized as the gold standard for diag…
Experimental demonstration of mice tumor control with a laser-accelerated high-energy electron radiotherapy prototype
Zhiyuan Guo, Shuang Liu, Bing Zhou +9
Radiotherapy using very-high-energy electron (VHEE) beams (50-300 MeV) has attracted considerable attention due to its advantageous dose deposition characteristics, enabling deep p…
Cross-modality Attention Adapter: A Glioma Segmentation Fine-tuning Method for SAM Using Multimodal Brain MR Images
Xiaoyu Shi, Shurong Chai, Yinhao Li +4
According to the 2021 World Health Organization (WHO) Classification scheme for gliomas, glioma segmentation is a very important basis for diagnosis and genotype prediction. In gen…
AMA-GCN: Adaptive Multi-layer Aggregation Graph Convolutional Network for Disease Prediction
Hao Chen, Fuzhen Zhuang, Li Xiao +5
Recently, Graph Convolutional Networks (GCNs) have proven to be a powerful mean for Computer Aided Diagnosis (CADx). This approach requires building a population graph to aggregate…