Combined global and local information for blind CT image quality assessment via deep learning-Reference-Cited by-同舟云学术

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Combined global and local information for blind CT image quality assessment via deep learning

Published:2020-03-16 Issue: Volume: Page:
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Container-title:Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment
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Author:

Gao Qi,Li Sui,Zhu Manman,Li Danyang,Bian Zhaoying,Lv Qingwen,Zeng Dong,Ma Jianhua

Publisher

SPIE

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. No-Reference Image Quality Assessment Based on Machine Learning and Outlier Entropy Samples;Pattern Recognition and Image Analysis;2024-06

2. Classifying Breast Tumors in Digital Tomosynthesis by Combining Image Quality-Aware Features and Tumor Texture Descriptors;Machine Learning and Knowledge Extraction;2024-03-11

3. GREAT- IQA: Integrating Global Perception and Local Task-Specific Information for CT Image Quality Assessment;2023 IEEE International Conference on Medical Artificial Intelligence (MedAI);2023-11-18

4. Deep Blind Chest X-Ray Image Quality Assessment With Region-of-Interest-Guided Attention;IEEE MultiMedia;2023-10

5. Applicability Evaluation of Full-Reference Image Quality Assessment Methods for Computed Tomography Images;Journal of Digital Imaging;2023-08-07

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