Xianghua Ye
According to our database1,
Xianghua Ye
authored at least 28 papers
between 2009 and 2024.
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Bibliography
2024
Low-Rank Continual Pyramid Vision Transformer: Incrementally Segment Whole-Body Organs in CT with Light-Weighted Adaptation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Slice-Consistent Lymph Nodes Detection Transformer in CT Scans via Cross-Slice Query Contrastive Learning.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Semi-supervised Lymph Node Metastasis Classification with Pathology-Guided Label Sharpening and Two-Streamed Multi-scale Fusion.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
Effective Lymph Nodes Detection in CT Scans Using Location Debiased Query Selection and Contrastive Query Representation in Transformer.
Proceedings of the Computer Vision - ECCV 2024, 2024
Bootstrapping Chest CT Image Understanding by Distilling Knowledge from X-Ray Expert Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
2023
SAMv2: A Unified Framework for Learning Appearance, Semantic and Cross-Modality Anatomical Embeddings.
CoRR, 2023
SAME++: A Self-supervised Anatomical eMbeddings Enhanced medical image registration framework using stable sampling and regularized transformation.
CoRR, 2023
CoRR, 2023
Accurate Airway Tree Segmentation in CT Scans via Anatomy-aware Multi-class Segmentation and Topology-guided Iterative Learning.
CoRR, 2023
Continual Segment: Towards a Single, Unified and Accessible Continual Segmentation Model of 143 Whole-body Organs in CT Scans.
CoRR, 2023
Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans.
CoRR, 2023
Automated Coarse-to-Fine Segmentation of Thoracic Duct Using Anatomy Priors and Topology-Guided Curved Planar Reformation.
Proceedings of the Machine Learning in Medical Imaging - 14th International Workshop, 2023
Parse and Recall: Towards Accurate Lung Nodule Malignancy Prediction Like Radiologists.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Anatomy-Aware Lymph Node Detection in Chest CT Using Implicit Station Stratification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops, 2023
SAMConvex: Fast Discrete Optimization for CT Registration Using Self-supervised Anatomical Embedding and Correlation Pyramid.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Continual Segment: Towards a Single, Unified and Non-forgetting Continual Segmentation Model of 143 Whole-body Organs in CT Scans.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
CancerUniT: Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
2022
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
Thoracic Lymph Node Segmentation in CT Imaging via Lymph Node Station Stratification and Size Encoding.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
2021
Comprehensive and Clinically Accurate Head and Neck Organs at Risk Delineation via Stratified Deep Learning: A Large-scale Multi-Institutional Study.
CoRR, 2021
Multi-institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume using planning-CT and FDG-PETCT.
CoRR, 2021
DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans using Anatomical Context Encoding and Key Organ Auto-Search.
CoRR, 2021
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans Using Anatomical Context Encoding and Key Organ Auto-Search.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
2020
Detecting Scatteredly-Distributed, Small, andCritically Important Objects in 3D OncologyImaging via Decision Stratification.
CoRR, 2020
Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-Based Gating Using 3D CT/PET Imaging in Radiotherapy.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
2009
Comput. Medical Imaging Graph., 2009