标题
Lymphoma segmentation from 3D PET-CT images using a deep evidential network
作者
关键词
-
出版物
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
Volume 149, Issue -, Pages 39-60
出版商
Elsevier BV
发表日期
2022-07-04
DOI
10.1016/j.ijar.2022.06.007
参考文献
相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。- Reproducibility of Baseline Tumour Metabolic Volume Measurements in Diffuse Large B-Cell LymphomA: Is There a Superior Method?
- (2021) Florian Eude et al. Metabolites
- Partial classification in the belief function framework
- (2021) Liyao Ma et al. KNOWLEDGE-BASED SYSTEMS
- Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods
- (2021) Eyke Hüllermeier et al. MACHINE LEARNING
- Evidential fully convolutional network for semantic segmentation
- (2021) Zheng Tong et al. APPLIED INTELLIGENCE
- NN-EVCLUS: Neural Network-based Evidential Clustering
- (2021) Thierry Denceux INFORMATION SCIENCES
- Fast semi-supervised evidential clustering
- (2021) Violaine Antoine et al. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
- An evidential classifier based on Dempster-Shafer theory and deep learning
- (2021) Zheng Tong et al. NEUROCOMPUTING
- Evidential instance selection for K-nearest neighbor classification of big data
- (2021) Chaoyu Gong et al. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
- Belief functions clustering for epipole localization
- (2021) Huiqin Chen et al. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
- Cautious classification based on belief functions theory and imprecise relabelling
- (2021) Abdelhak Imoussaten et al. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
- Analyzing the Quality and Challenges of Uncertainty Estimations for Brain Tumor Segmentation
- (2020) Alain Jungo et al. Frontiers in Neuroscience
- Quantifying and Leveraging Predictive Uncertainty for Medical Image Assessment
- (2020) Florin C. Ghesu et al. MEDICAL IMAGE ANALYSIS
- Logistic regression, neural networks and Dempster-Shafer theory: A new perspective
- (2019) Thierry Denœux KNOWLEDGE-BASED SYSTEMS
- Decision-making with belief functions: A review
- (2019) Thierry Denœux INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
- A new evidential K-nearest neighbor rule based on contextual discounting with partially supervised learning
- (2019) Thierry Denœux et al. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
- Detection and segmentation of lymphomas in 3D PET images via clustering with entropy-based optimization strategy
- (2019) Haigen Hu et al. International Journal of Computer Assisted Radiology and Surgery
- Defining the optimal method for measuring baseline metabolic tumour volume in diffuse large B cell lymphoma
- (2018) Hajira Ilyas et al. EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
- Joint Tumor Segmentation in PET-CT Images Using Co-Clustering and Fusion Based on Belief Functions
- (2018) Chunfeng Lian et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research
- (2017) Ziv Yaniv et al. JOURNAL OF DIGITAL IMAGING
- Proposition and learning of some belief function contextual correction mechanisms
- (2016) Frédéric Pichon et al. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
- Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm
- (2014) D.P. Onoma et al. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
- The Design of SimpleITK
- (2013) Bradley C. Lowekamp et al. Frontiers in Neuroinformatics
- PET-guided delineation of radiation therapy treatment volumes: a survey of image segmentation techniques
- (2010) Habib Zaidi et al. EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
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