Yury Velichko

Orcid: 0000-0002-2287-5727

According to our database1, Yury Velichko authored at least 23 papers between 2023 and 2025.

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

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2025
Large-scale multi-center CT and MRI segmentation of pancreas with deep learning.
Medical Image Anal., 2025

2024
Adaptive Aggregation Weights for Federated Segmentation of Pancreas MRI.
CoRR, 2024

A Novel Momentum-Based Deep Learning Techniques for Medical Image Classification and Segmentation.
CoRR, 2024

Brain Tumor Segmentation (BraTS) Challenge 2024: Meningioma Radiotherapy Planning Automated Segmentation.
CoRR, 2024

The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRI.
CoRR, 2024

Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge.
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CoRR, 2024

MDNet: Multi-Decoder Network for Abdominal CT Organs Segmentation.
CoRR, 2024

PAM-UNet: Shifting Attention on Region of Interest in Medical Images.
CoRR, 2024

Detection of Peri-Pancreatic Edema using Deep Learning and Radiomics Techniques.
CoRR, 2024

A Probabilistic Hadamard U-Net for MRI Bias Field Correction.
CoRR, 2024

Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

A Probabilistic Hadamard U-Net for MRI Bias Field Correction.
Proceedings of the Machine Learning in Medical Imaging - 15th International Workshop, 2024

A Novel Momentum-Based Deep Learning Techniques for Medical Image Classification and Segmentation.
Proceedings of the Machine Learning in Medical Imaging - 15th International Workshop, 2024

Adaptive Smooth Activation Function for Improved Organ Segmentation and Disease Diagnosis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Fusenet: Self-Supervised Dual-Path Network For Medical Image Segmentation.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Leveraging Unlabeled Data for 3D Medical Image Segmentation Through Self-Supervised Contrastive Learning.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

CT Liver Segmentation Via PVT-Based Encoding and Refined Decoding.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

HCA-NET: Hierarchical Context Attention Network for Intervertebral Disc Semantic Labeling.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

2023
Adaptive Smooth Activation for Improved Disease Diagnosis and Organ Segmentation from Radiology Scans.
CoRR, 2023

A multi-institutional pediatric dataset of clinical radiology MRIs by the Children's Brain Tumor Network.
CoRR, 2023

The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma.
CoRR, 2023

Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Self-supervised Semantic Segmentation: Consistency over Transformation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023


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