Ke Yan

According to our database1, Ke Yan authored at least 26 papers between 2017 and 2020.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2020
Learning from Multiple Datasets with Heterogeneous and Partial Labels for Universal Lesion Detection in CT.
CoRR, 2020

One Click Lesion RECIST Measurement and Segmentation on CT Scans.
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

Lesion Harvester: Iteratively Mining Unlabeled Lesions and Hard-Negative Examples at Scale.
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

One Click Lesion RECIST Measurement and Segmentation on CT Scans.
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


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