Ke Yan
Affiliations:- National Institutes of Health Clinical Center, Bethesda, USA
According to our database1,
Ke Yan
authored at least 59 papers
between 2017 and 2024.
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Bibliography
2024
Towards a Comprehensive, Efficient and Promptable Anatomic Structure Segmentation Model using 3D Whole-body CT Scans.
CoRR, 2024
Modality-Agnostic Structural Image Representation Learning for Deformable Multi-Modality Medical Image Registration.
CoRR, 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
CoRR, 2023
A Cascaded Approach for ultraly High Performance Lesion Detection and False Positive Removal in Liver CT Scans.
CoRR, 2023
Anatomical Invariance Modeling and Semantic Alignment for Self-supervised Learning in 3D Medical Image Segmentation.
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
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
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Anatomical Invariance Modeling and Semantic Alignment for Self-supervised Learning in 3D Medical Image Analysis.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 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
Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation and Out-of-Distribution Localization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
SAM: Self-Supervised Learning of Pixel-Wise Anatomical Embeddings in Radiological Images.
IEEE Trans. Medical Imaging, 2022
CoRR, 2022
A New Probabilistic V-Net Model with Hierarchical Spatial Feature Transform for Efficient Abdominal Multi-Organ Segmentation.
CoRR, 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
Learning From Multiple Datasets With Heterogeneous and Partial Labels for Universal Lesion Detection in CT.
IEEE Trans. Medical Imaging, 2021
Lesion-Harvester: Iteratively Mining Unlabeled Lesions and Hard-Negative Examples at Scale.
IEEE Trans. Medical Imaging, 2021
Accurate and Generalizable Quantitative Scoring of Liver Steatosis from Ultrasound Images via Scalable Deep Learning.
CoRR, 2021
CoRR, 2021
Lesion Segmentation and RECIST Diameter Prediction via Click-Driven Attention and Dual-Path Connection.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Sequential Learning on Liver Tumor Boundary Semantics and Prognostic Biomarker Mining.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
2020
Automated abnormality classification of chest radiographs using deep convolutional neural networks.
npj Digit. Medicine, 2020
CoRR, 2020
Learning from Multiple Datasets with Heterogeneous and Partial Labels for Universal Lesion Detection in CT.
CoRR, 2020
Harvesting, Detecting, and Characterizing Liver Lesions from Large-scale Multi-phase CT Data via Deep Dynamic Texture Learning.
CoRR, 2020
Universal Lesion Detection by Learning from Multiple Heterogeneously Labeled Datasets.
CoRR, 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
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
Reliable Liver Fibrosis Assessment from Ultrasound Using Global Hetero-Image Fusion and View-Specific Parameterization.
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
Deep Volumetric Universal Lesion Detection Using Light-Weight Pseudo 3D Convolution and Surface Point Regression.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
2019
ULDor: A Universal Lesion Detector for CT Scans with Pseudo Masks and Hard Negative Example Mining.
CoRR, 2019
MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Fine-Grained Lesion Annotation in CT Images With Knowledge Mined From Radiology Reports.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019
Uldor: A Universal Lesion Detector For Ct Scans With Pseudo Masks And Hard Negative Example Mining.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019
A self-attention based deep learning method for lesion attribute detection from CT reports.
Proceedings of the 2019 IEEE International Conference on Healthcare Informatics, 2019
Holistic and Comprehensive Annotation of Clinically Significant Findings on Diverse CT Images: Learning From Radiology Reports and Label Ontology.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019
Deep Lesion Graph in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-Scale Lesion Database.
Proceedings of the Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics, 2019
2018
Accurate Weakly Supervised Deep Lesion Segmentation on CT Scans: Self-Paced 3D Mask Generation from RECIST.
CoRR, 2018
3D Context Enhanced Region-Based Convolutional Neural Network for End-to-End Lesion Detection.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement.
Proceedings of the Machine Learning in Medical Imaging - 9th International Workshop, 2018
Accurate Weakly-Supervised Deep Lesion Segmentation Using Large-Scale Clinical Annotations: Slice-Propagated 3D Mask Generation from 2D RECIST.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
Unsupervised body part regression via spatially self-ordering convolutional neural networks.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
Deep Lesion Graphs in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-Scale Lesion Database.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018
2017
DeepLesion: Automated Deep Mining, Categorization and Detection of Significant Radiology Image Findings using Large-Scale Clinical Lesion Annotations.
CoRR, 2017
Unsupervised body part regression using convolutional neural network with self-organization.
CoRR, 2017