Shenghong Ju

Orcid: 0000-0001-5041-7865

According to our database1, Shenghong Ju authored at least 13 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Maturation and reorganization of structural connectivity in infants within half a year.
NeuroImage, 2026

2025
Multimodal Human-AI Synergy for Medical Imaging Quality Control: A Hybrid Intelligence Framework with Adaptive Dataset Curation and Closed-Loop Evaluation.
CoRR, March, 2025

Retinopathy identification in optical coherence tomography images based on a novel class-aware contrastive learning approach.
Knowl. Based Syst., 2025

SDS-Net: A Synchronized Dual-Stage Network for Predicting Patients Within 4.5-h Thrombolytic Treatment Window Using MRI.
J. Imaging Inform. Medicine, 2025

CECT-Mamba: A Hierarchical Contrast-Enhanced-Aware Model for Pancreatic Tumor Subtyping from Multi-Phase CECT.
Proceedings of the IEEE/CVF International Conference on Computer Vision, ICCV 2025, 2025

2024
Trustworthy multi-phase liver tumor segmentation via evidence-based uncertainty.
Eng. Appl. Artif. Intell., 2024

2022
Designing thermal radiation metamaterials via hybrid adversarial autoencoder and Bayesian optimization.
CoRR, 2022

ISP-Net: Fusing features to predict ischemic stroke infarct core on CT perfusion maps.
Comput. Methods Programs Biomed., 2022

An Investigation of the Impacts of Three Anesthetic Regimens on Task-Functional Magnetic Resonance Imaging and Functional Connectivity Resting-State Functional Magnetic Resonance Imaging in Sprague Dawley and Wistar Rats.
Brain Connect., 2022

2020
CT Super-Resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble (GAN-CIRCLE).
IEEE Trans. Medical Imaging, 2020

2018
CT Super-resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble(GAN-CIRCLE).
CoRR, 2018

Structure-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising.
CoRR, 2018

Structurally-Sensitive Multi-Scale Deep Neural Network for Low-Dose CT Denoising.
IEEE Access, 2018


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