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For: Gillmann C, Saur D, Wischgoll T, Scheuermann G. Uncertainty‐aware Visualization in Medical Imaging ‐ A Survey. Computer Graphics Forum 2021;40:665-89. [DOI: 10.1111/cgf.14333] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
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1 Musleh M, Muren LP, Toussaint L, Vestergaard A, Gröller E, Raidou RG. Uncertainty guidance in proton therapy planning visualization. Computers & Graphics 2023. [DOI: 10.1016/j.cag.2023.02.002] [Reference Citation Analysis]
2 Maack RGC, Scheuermann G, Hagen H, Peñaloza JTH, Gillmann C. Uncertainty-aware visual analytics: scope, opportunities, and challenges. Vis Comput 2022. [DOI: 10.1007/s00371-022-02733-6] [Reference Citation Analysis]
3 Gruen J, van der Voort G, Schultz T. Model Averaging and Bootstrap Consensus‐based Uncertainty Reduction in Diffusion MRI Tractography. Computer Graphics Forum 2022. [DOI: 10.1111/cgf.14724] [Reference Citation Analysis]
4 Andújar C, Brunet P, Chica A, Navazo I, Vinacua À. Solid Modelling for Manufacturing: From Voelcker’s Boundary Evaluation to Discrete Paradigms. Computer-Aided Design 2022;152:103370. [DOI: 10.1016/j.cad.2022.103370] [Reference Citation Analysis]
5 Bierbrier J, Gueziri HE, Collins DL. Estimating medical image registration error and confidence: A taxonomy and scoping review. Med Image Anal 2022;81:102531. [PMID: 35858506 DOI: 10.1016/j.media.2022.102531] [Reference Citation Analysis]
6 Akyel C, Arıcı N. LinkNet-B7: Noise Removal and Lesion Segmentation in Images of Skin Cancer. Mathematics 2022;10:736. [DOI: 10.3390/math10050736] [Cited by in Crossref: 2] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
7 Gillmann C, Saur D, Scheuermann G. How to deal with Uncertainty in Machine Learning for Medical Imaging? 2021 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX) 2021. [DOI: 10.1109/trex53765.2021.00014] [Reference Citation Analysis]