A Novel Quality Control Algorithm for Medical Image Segmentation Based on Fuzzy Uncertainty
Author:
Affiliation:
1. Laboratory for Uncertainty in Data and Decision Making and the Intelligent Modelling and Analysis, University of Nottingham, Nottingham, U.K.
Funder
School of Computer Science, the University of Nottingham
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/91/4358784/09980452.pdf?arnumber=9980452
Cited by 6 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. A review of uncertainty quantification in medical image analysis: Probabilistic and non-probabilistic methods;Medical Image Analysis;2024-10
2. Uncertainty Aware Segmentation Quality Assessment in Medical Images;2024 IEEE International Symposium on Biomedical Imaging (ISBI);2024-05-27
3. FMPNet: a fuzzy-embedded multi-scale prototype network for sea-land segmentation of remote sensing images;European Journal of Remote Sensing;2024-04-25
4. Trustworthy clinical AI solutions: A unified review of uncertainty quantification in Deep Learning models for medical image analysis;Artificial Intelligence in Medicine;2024-04
5. Hybrid Intelligent Pattern Recognition Systems for Mass Segmentation and Classification: A Pilot Study on Full-Field Digital Mammograms;Applied Sciences;2023-09-17
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