Titlebook: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging; 5th International Wo Carole H. Sudre,Christian F. Baumgartner,Will

谦虚的人

placebo-effect

,Uncertainty Estimation in Liver Tumor Segmentation Using the Posterior Bootstrap,sterior bootstrap method provides improvement on uncertainty estimation with equivalent segmentation performance. The proposed method is easy to implement, compatible with any deep learning-based image segmentation pipeline, and doesn’t require additional hyper-parameter tuning, enabling it to total

征税

混合

https://doi.org/10.1007/978-3-031-44336-7Uncertainty modelling; Machine learning; Medical Imaging; Uncertainty calibration; artificial intelligen

有恶臭

978-3-031-44335-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

发展

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging978-3-031-44336-7Series ISSN 0302-9743 Series E-ISSN 1611-3349

CLAP

Obligatory

,Numerical Uncertainty of Convolutional Neural Networks Inference for Structural Brain MRI Analysis,-linear registration: 19 vs 13 significant bits on average; whole-brain segmentation: 0.99 vs 0.92 Sørensen-Dice score on average), which suggests a better reproducibility of CNN results across execution environments.

拉开这车床

Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image Segmentation,leneck features with principal component analysis, images the model failed on were detected with high performance and minimal computational load. Specifically, the proposed technique achieved 92% area under the receiver operating characteristic curve and 94% area under the precision-recall curve and can run in seconds on a central processing unit.

Sciatica

Conference proceedings 2023publication. The accepted papers cover the fields of uncertainty estimation and modeling, as well as out of distribution management, domain shift robustness, Bayesian deep learning and uncertainty calibration..