Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis : 3rd International Workshop, UNSURE 2021, and 6th International Workshop, PIPPI 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings / edited by Carole H. Sudre, Roxane Licandro, Christian Baumgartner, Andrew Melbourne, Adrian Dalca, Jana Hutter, Ryutaro Tanno, Esra Abaci Turk, Koen Van Leemput, Jordina Torrents Barrena, William M. Wells, Christopher Macgowan.

Format:

Book

Contributor:

Sudre, Carole H., Editor.

Licandro, Roxane, Editor.

Baumgartner, Christian, Editor.

Melbourne, Andrew, Editor.

Dalca, Adrian., Editor.

Hutter, Jana, Editor.

Tanno, Ryutaro, Editor.

Abaci Turk, Esra., Editor.

Van Leemput, Koen., Editor.

Torrents Barrena, Jordina., Editor.

Wells, William M., Editor.

Macgowan, Christopher., Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 12959

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 12959

Language:

English

Subjects (All):

Artificial intelligence.

Computer vision.

Bioinformatics.

Pattern recognition systems.

Artificial Intelligence.

Computer Vision.

Computational and Systems Biology.

Automated Pattern Recognition.

Local Subjects:

Artificial Intelligence.

Computer Vision.

Computational and Systems Biology.

Automated Pattern Recognition.

Physical Description:

1 online resource (XIII, 296 pages) : 112 illustrations, 103 illustrations in color.

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

This book constitutes the refereed proceedings of the Third International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2021, and the 6th International Workshop on Preterm, Perinatal and Paediatric Image Analysis, PIPPI 2021, held in conjunction with MICCAI 2021. The conference was planned to take place in Strasbourg, France, but was held virtually due to the COVID-19 pandemic.For UNSURE 2021, 13 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world. PIPPI 2021 accepted 14 papers from the 18 submissions received. The workshop aims to bring together methods and experience from researchers and authors working on these younger cohorts and provides a forum for the open discussion of advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period.

Contents:

UNSURE 2021 - Uncertainty estimation and modelling and annotation uncertainty

Model uncertainty estimation for medical Imaging based diagnosis

Accurate simulation of operating system updates in neuroimaging using Monte-Carlo arithmetic

Leveraging uncertainty estimates to improve segmentation performance in cardiac MR

Improving the reliability of semantic segmentation of medical images by uncertainty modelling with Bayesian deep networks and curriculum learning

Unpaired MR image homogeneisation by disentangled representations and its uncertainty

Uncertainty-aware deep learning based deformable registration

Monte Carlo Concrete DropPath for Epistemic Uncertainty Estimation in Brain Tumour segmentation

Improving Aleatoric Uncertainty quantification in multi-annotated medical image segmentation with normalizing flows

UNSURE 2021 - Domain shift robustness and risk management in clinical pipelines

Task-agnostic out-of-distribution detection using kernel density estimation

Out of distribution detection for medical images

Robust selective classification of skin lesions with asymmetric costs

Confidence-based Out-of-Distribution detection: a comparative study and analysis

Novel disease detection using ensembles with regularized disagreement

PIPPI2021

Automatic Placenta Abnormality Detection using Convolutional Neural Networks on Ultrasound Texture

Simulated Half-Fourier Acquisitions Single-shot Turbo Spin Echo (HASTE) of the Fetal Brain: Application to Super-Resolution Reconstruction

Spatio-temporal atlas of normal fetal craniofacial feature development and CNN-based ocular biometry for motion-corrected fetal MRI

Myelination of preterm brain networks at adolescence

A bootstrap self-training method for sequence transfer: State-of-the-art placenta segmentation in fetal MRI

Segmentation of the cortical plate in fetal brain MRI with a topological loss

Fetal brain MRI measurements using a deep learning landmark network with reliability estimation

CAS-Net: Conditional Atlas Generation and Brain Segmentation for Fetal MRI

Detection of Injury and Automated Triage of Preterm Neonatal MRI using Patch-Based Gaussian Processes

Assessment of Regional Cortical Development through Fissure Based Gestational Age Estimation in 3D Fetal Ultrasound

Texture-based Analysis of Fetal Organs in Fetal Growth Restriction

Distributionally Robust Segmentation of Abnormal Fetal Brain 3D MRI

Analysis of the Anatomical Variability of Fetal Brains with Corpus Callosum Agenesis

Predicting preterm birth using multimodal fetal imaging.

Other Format:

Printed edition:

ISBN:

978-3-030-87735-4

9783030877354

Access Restriction:

Restricted for use by site license.