Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis

Second International Workshop, UNSURE 2020, and Third International Workshop, GRAIL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings

AvCarole H. Sudre,Hamid Fehri

Häftad, Engelska, 2020

Del 12443 i serien Lecture Notes in Computer Science

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Beskrivning

This book constitutes the refereed proceedings of the Second International Workshop on Uncertainty for Safe Utilization of Machine Learning 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.

Produktinformation

Utgivningsdatum:2020-10-06
Mått:155 x 235 x 14 mm
Vikt:376 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:222
Förlag:Springer Nature Switzerland AG
ISBN:9783030603649

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT
Tillämpad datateknik inom Data och IT

Innehållsförteckning

UNSURE 2020.- Image registration via stochastic gradient Markov chain Monte Carlo.- RevPHiSeg: A Memory-Efficient Neural Network for Uncertainty Quantification.- Hierarchical brain parcellation with uncertainty.- Quantitative Comparison of Monte-Carlo Dropout Uncertainty Measures for Multi-Class Segmentation.- Uncertainty Estimation in Landmark Localization based on Gaussian Heatmaps.- Weight averaging impact on the uncertainty of retinal artery-venous segmentation.- Improving Pathological Distribution Measurements with Bayesian Uncertainty.- Improving Reliability of Clinical Models using Prediction Calibration.- Uncertainty Estimation in Medical Image Denoising with Bayesian Deep Image Prior.- Uncertainty Estimation for Assessment of 3D US Scan Adequacy and DDH Metric Reliability.- GRAIL 2020.- Clustering-based Deep Brain MultiGraph Integrator Network for Learning Connectional Brain Templates.- Detection of Discriminative Neurological Circuits Using Hierarchical GraphConvolutional Networks in fMRI Sequences.- Graph Matching Based Connectomic Biomarker with Learning for Brain Disorders.- Multi-Scale Profiling of Brain Multigraphs by Eigen-based Cross-Diffusion and Heat Tracing for Brain State Proling.- Graph Domain Adaptation for Alignment-Invariant Brain Surface Segmentation.- Min-cut Max-flow for Network Abnormality Detection: Application to Preterm Birth.- Geometric Deep Learning for Post-Menstrual Age Prediction based on the Neonatal White Matter Cortical Surface.- The GraphNet Zoo: An All-in-One Graph Based Deep Semi-Supervised Framework for Medical Image Classification.- Intraoperative Liver Surface Completion with Graph Convolutional VAE.- HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification.

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Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis

Second International Workshop, UNSURE 2020, and Third International Workshop, GRAIL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings

Beskrivning

Produktinformation

Utforska kategorier

Innehållsförteckning

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