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  • Produktbild: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis
  • Produktbild: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis
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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

Aus der Reihe Lecture Notes in Computer Science

Fr. 93.90

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.10.2021

Herausgeber

Roxane Licandro + weitere

Verlag

Springer

Seitenzahl

296

Maße (L/B/H)

23.5/15.5/1.7 cm

Gewicht

476 g

Auflage

1st ed. 2021

Sprache

Englisch

ISBN

978-3-030-87734-7

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

01.10.2021

Herausgeber

Verlag

Springer

Seitenzahl

296

Maße (L/B/H)

23.5/15.5/1.7 cm

Gewicht

476 g

Auflage

1st ed. 2021

Sprache

Englisch

ISBN

978-3-030-87734-7

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis
  • Produktbild: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis
  • 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.