Liying Peng

Orcid: 0000-0001-5713-8981

According to our database1, Liying Peng authored at least 10 papers between 2016 and 2022.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2022
DeepRecS: From RECIST Diameters to Precise Liver Tumor Segmentation.
IEEE J. Biomed. Health Informatics, 2022

2021
Multi-phase Liver Tumor Segmentation with Spatial Aggregation and Uncertain Region Inpainting.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020
Semi-Supervised Learning for Semantic Segmentation of Emphysema With Partial Annotations.
IEEE J. Biomed. Health Informatics, 2020

Storage Reliability Evaluation based on Competing Risks of Degradation Failure and Random Failure for Missiles.
Proceedings of the WSSE 2020: The 2nd World Symposium on Software Engineering, 2020

Multi-modal Perceptual Adversarial Learning for Longitudinal Prediction of Infant MR Images.
Proceedings of the Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis, 2020

2019
Classification and Quantification of Emphysema Using a Multi-Scale Residual Network.
IEEE J. Biomed. Health Informatics, 2019

2018
Multi-scale Residual Network with Two Channels of Raw CT Image and Its Differential Excitation Component for Emphysema Classification.
Proceedings of the Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support, 2018

Classification of Pulmonary Emphysema in CT Images Based on Multi-Scale Deep Convolutional Neural Networks.
Proceedings of the 2018 IEEE International Conference on Image Processing, 2018

2017
Joint weber-based rotation invariant uniform local ternary pattern for classification of pulmonary emphysema in CT images.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

2016
Single Image Super-Resolution via Convolutional Neural Network and Total Variation Regularization.
Proceedings of the MultiMedia Modeling - 22nd International Conference, 2016


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