Ju Zhang

Orcid: 0000-0003-3412-6448

Affiliations:
  • Zhejiang University of Technology, Hangzhou, China


According to our database1, Ju Zhang authored at least 26 papers between 2015 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Interpretable deep learning enables reliable and label-efficient fluorescence imaging.
Pattern Recognit., 2026

UniMedX: A Unified Kolmogorov-Arnold Theory Guided Framework for Interpretable Medical Image Classification and Segmentation.
Knowl. Based Syst., 2026

A novel window-based hybrid attention network for low-dose CT image denoising.
Complex Intell. Syst., 2026

Residual-guided multiscale diffusion model for low-dose CT denoising.
Biomed. Signal Process. Control., 2026

2025
A Novel Network for Low-Dose CT Denoising Based on Dual-Branch Structure and Multi-Scale Residual Attention.
J. Imaging Inform. Medicine, 2025

A Novel Network With Spectrum Transformer and Triplet Attention for CT Image Segmentation.
Int. J. Imaging Syst. Technol., 2025

Multi-scale adaptive residual cold diffusion model for Low-Dose CT denoising.
Expert Syst. Appl., 2025

TransGraphNet: A novel network for medical image segmentation based on transformer and graph convolution.
Biomed. Signal Process. Control., 2025

2024
A Review of deep learning methods for denoising of medical low-dose CT images.
Comput. Biol. Medicine, 2024

Recent developments in segmentation of COVID-19 CT images using deep-learning: An overview of models, techniques and challenges.
Biomed. Signal Process. Control., 2024

2023
A novel denoising method for low-dose CT images based on transformer and CNN.
Comput. Biol. Medicine, September, 2023

CdcSegNet: Automatic COVID-19 Infection Segmentation From CT Images.
IEEE Trans. Instrum. Meas., 2023

A novel denoising method for CT images based on U-net and multi-attention.
Comput. Biol. Medicine, 2023

2022
Multi-scale aggregation networks with flexible receptive fields for melanoma segmentation.
Biomed. Signal Process. Control., September, 2022

A Novel Denoising Method for Medical CT Images Based on Moving Decomposition Framework.
Circuits Syst. Signal Process., 2022

2021
CNN and multi-feature extraction based denoising of CT images.
Biomed. Signal Process. Control., 2021

Dense GAN and multi-layer attention based lesion segmentation method for COVID-19 CT images.
Biomed. Signal Process. Control., 2021

2020
Grid k-d tree approach for point location in polyhedral data sets - application to explicit MPC.
Int. J. Control, 2020

A Novel Despeckling Method for Medical Ultrasound Images Based on the Nonsubsampled Shearlet and Guided Filter.
Circuits Syst. Signal Process., 2020

2019
2DRLPP: Robust two-dimensional locality preserving projection with regularization.
Knowl. Based Syst., 2019

A Trace Lasso Regularized Robust Nonparallel Proximal Support Vector Machine for Noisy Classification.
IEEE Access, 2019

2018
K-d tree based approach for point location problem in explicit model predictive control.
J. Frankl. Inst., 2018

Robust <i>L</i><sub>1</sub>-norm multi-weight vector projection support vector machine with efficient algorithm.
Neurocomputing, 2018

2017
An Integrated De-speckling Approach for Medical Ultrasound Images Based on Wavelet and Trilateral Filter.
Circuits Syst. Signal Process., 2017

2015
Comparison of Despeckle Filters for Breast Ultrasound Images.
Circuits Syst. Signal Process., 2015

Wavelet and fast bilateral filter based de-speckling method for medical ultrasound images.
Biomed. Signal Process. Control., 2015


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