Ziyang Chen

Orcid: 0000-0002-8564-9735

Affiliations:
  • Northwestern Polytechnical University, Xi'an, China


According to our database1, Ziyang Chen authored at least 25 papers between 2021 and 2025.

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

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2025
Enjoying Information Dividend: Gaze Track-based Medical Weakly Supervised Segmentation.
CoRR, May, 2025

CADS: A Self-Supervised Learner via Cross-Modal Alignment and Deep Self-Distillation for CT Volume Segmentation.
IEEE Trans. Medical Imaging, January, 2025

SegRap2023: A benchmark of organs-at-risk and gross tumor volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma.
Medical Image Anal., 2025

Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Gradient Alignment Improves Test-Time Adaptation for Medical Image Segmentation.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
TriLA: Triple-Level Alignment Based Unsupervised Domain Adaptation for Joint Segmentation of Optic Disc and Optic Cup.
IEEE J. Biomed. Health Informatics, September, 2024

Meta Curvature-Aware Minimization for Domain Generalization.
CoRR, 2024

CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation.
CoRR, 2024

Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
CoRR, 2024

Day-Night Adaptation: An Innovative Source-free Adaptation Framework for Medical Image Segmentation.
CoRR, 2024

MedUniSeg: 2D and 3D Medical Image Segmentation via a Prompt-driven Universal Model.
CoRR, 2024

Pre-training Everywhere: Parameter-Efficient Fine-Tuning for Medical Image Analysis via Target Parameter Pre-training.
CoRR, 2024

From Few to More: Scribble-based Medical Image Segmentation via Masked Context Modeling and Continuous Pseudo Labels.
CoRR, 2024


DyNo: Dynamic Normalization based Test-Time Adaptation for 2D Medical Image Segmentation.
Proceedings of the Machine Learning in Medical Imaging - 15th International Workshop, 2024

Rethinking nnU-Net for Cross-Modality Unsupervised Domain Adaptation in Abdominal Organ Segmentation.
Proceedings of the Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation, 2024

Reframing Universal Lesion Segmentation as a Large-Organ Lesion Segmentation Task.
Proceedings of the Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation, 2024

Continual Self-Supervised Learning: Towards Universal Multi-Modal Medical Data Representation Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image Segmentation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Reconstruction-Driven Dynamic Refinement Based Unsupervised Domain Adaptation for Joint Optic Disc and Cup Segmentation.
IEEE J. Biomed. Health Informatics, July, 2023

UniSeg: A Prompt-Driven Universal Segmentation Model as Well as A Strong Representation Learner.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Treasure in Distribution: A Domain Randomization Based Multi-source Domain Generalization for 2D Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

2022
DeSD: Self-Supervised Learning with Deep Self-Distillation for 3D Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Encoding Deep Residual Features into Fisher Vector for Skin Lesion Classification.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

2021
CDLRS: Collaborative Deep Learning Model with Joint Regression and Segmentation for Automatic Fovea Localization.
Proceedings of the Ophthalmic Medical Image Analysis - 8th International Workshop, 2021


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