Titlebook: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Im; Second International Carole H. Sudre,

Crohns-disease

Geometric Deep Learning for Post-Menstrual Age Prediction Based on the Neonatal White Matter Cortica approach to predict the post-menstrual age (PA) at scan, using techniques from geometric deep learning, based on the neonatal white matter cortical surface. We utilize and compare multiple specialized neural network architectures that predict the age using different geometric representations of the

Benzodiazepines

伤心

妨碍

Quantitative Comparison of Monte-Carlo Dropout Uncertainty Measures for Multi-class Segmentationty measures based on the relevance of the uncertainty map to predict misclassification. Four uncertainty metrics were compared over a set of 144 models. The application studied is the segmentation of the lumen and vessel wall of carotid arteries based on multiple sequences of magnetic resonance (MR) images in multi-center data.

突袭

OPINE

Min-Cut Max-Flow for Network Abnormality Detection: Application to Preterm Birthly preterm born individuals. We show the feasibility to cast the network abnormality detection problem into a min-cut max-flow problem, and identify consistent abnormal white matter tracts in extremely preterm subjects, including a common network involving the bilateral thalamus and frontal gyri.

garrulous

Buttress

流浪者

蘑菇

0302-9743 in Medical Imaging, UNSURE 2020, and the Third International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic..For UNSURE 2020, 10 papers from 18 submissio