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Ben Glocker

Showing results (121-130 of 132) with videos related to

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Journal of Medical Imaging (Bellingham, Wash.)|October 26, 2020
Deep neural network to locate and segment brain tumors outperformed the expert technicians who created the training dataJoseph Ross Mitchell, Konstantinos Kamnitsas, Kyle W Singleton, et al.
Medical Image Analysis|August 1, 2016
ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRIOskar Maier, Bjoern H Menze, Janina von der Gablentz, et al.
The Lancet. Digital Health|December 19, 2024
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendationsJoseph E Alderman, Joanne Palmer, Elinor Laws, et al.
IEEE Transactions on Medical Imaging|June 3, 2011
Evaluation of registration methods on thoracic CT: the EMPIRE10 challengeKeelin Murphy, Bram van Ginneken, Joseph M Reinhardt, et al.
BMJ (Clinical Research Ed.)|February 5, 2025
FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcareKarim Lekadir, Alejandro F Frangi, Antonio R Porras, et al.
Medical Image Analysis|August 2, 2021
VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT imagesAnjany Sekuboyina, Malek E Husseini, Amirhossein Bayat, et al.
IEEE Transactions on Medical Imaging|December 11, 2014
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)Bjoern H Menze, Andras Jakab, Stefan Bauer, et al.
Nature Methods|February 12, 2024
Understanding metric-related pitfalls in image analysis validationAnnika Reinke, Minu D Tizabi, Michael Baumgartner, et al.
Nature Methods|February 12, 2024
Metrics reloaded: recommendations for image analysis validationLena Maier-Hein, Annika Reinke, Patrick Godau, et al.
Arxiv|March 22, 2023
Understanding metric-related pitfalls in image analysis validationAnnika Reinke, Minu D Tizabi, Michael Baumgartner, et al.
Pageof 14

Showing results (121-130 of 132) with videos related to

Sort By:
Pageof 14
Journal of Medical Imaging (Bellingham, Wash.)|October 26, 2020
Deep neural network to locate and segment brain tumors outperformed the expert technicians who created the training dataJoseph Ross Mitchell, Konstantinos Kamnitsas, Kyle W Singleton, et al.
Medical Image Analysis|August 1, 2016
ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRIOskar Maier, Bjoern H Menze, Janina von der Gablentz, et al.
The Lancet. Digital Health|December 19, 2024
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendationsJoseph E Alderman, Joanne Palmer, Elinor Laws, et al.
IEEE Transactions on Medical Imaging|June 3, 2011
Evaluation of registration methods on thoracic CT: the EMPIRE10 challengeKeelin Murphy, Bram van Ginneken, Joseph M Reinhardt, et al.
BMJ (Clinical Research Ed.)|February 5, 2025
FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcareKarim Lekadir, Alejandro F Frangi, Antonio R Porras, et al.
Medical Image Analysis|August 2, 2021
VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT imagesAnjany Sekuboyina, Malek E Husseini, Amirhossein Bayat, et al.
IEEE Transactions on Medical Imaging|December 11, 2014
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)Bjoern H Menze, Andras Jakab, Stefan Bauer, et al.
Nature Methods|February 12, 2024
Understanding metric-related pitfalls in image analysis validationAnnika Reinke, Minu D Tizabi, Michael Baumgartner, et al.
Nature Methods|February 12, 2024
Metrics reloaded: recommendations for image analysis validationLena Maier-Hein, Annika Reinke, Patrick Godau, et al.
Arxiv|March 22, 2023
Understanding metric-related pitfalls in image analysis validationAnnika Reinke, Minu D Tizabi, Michael Baumgartner, et al.
Pageof 14