Application of Automatic Segmentation on Super-Resolution Reconstruction MR Images of the Abnormal Fetal Brain Article Swipe

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Thomas Deprest , Lucas Fidon , Frederik De Keyzer , Michael Ebner , Jan Deprest , Philippe Demaerel , Luc De Catte , Tom Vercauteren , Sébastien Ourselin , Steven Dymarkowski , Michaël Aertsen ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.3174/ajnr.a7808

Our novel segmentation algorithm obtained excellent results on MR images of fetuses with severe brain abnormalities. Analysis of the outliers shows the need to include pathologies underrepresented in the current data set. Quality control to prevent occasional errors is still needed.

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Medicine

Segmentation Fault

Artificial Intelligence

Fetus

Computer Vision

Grey's Anatomy Season 18

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Medicine Segmentation Artificial intelligence Resolution (logic) Fetus Computer vision Anatomy Pattern recognition (psychology) Radiology Nuclear medicine Pregnancy Computer science Genetics Biology

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Type: article
Language: en
Landing Page: https://doi.org/10.3174/ajnr.a7808
OA Status: hybrid
Cited By: 5
References: 24
Related Works: 10
OpenAlex ID: https://openalex.org/W4323036703

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DOI: https://doi.org/10.3174/ajnr.a7808

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Title: Application of Automatic Segmentation on Super-Resolution Reconstruction MR Images of the Abnormal Fetal Brain

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Language: en

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Publication year: 2023

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Publication date: 2023-03-02

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Authors: Thomas Deprest, Lucas Fidon, Frederik De Keyzer, Michael Ebner, Jan Deprest, Philippe Demaerel, Luc De Catte, Tom Vercauteren, Sébastien Ourselin, Steven Dymarkowski, Michaël Aertsen

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Landing page: https://doi.org/10.3174/ajnr.a7808

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OA URL: https://doi.org/10.3174/ajnr.a7808

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Concepts: Medicine, Segmentation, Artificial intelligence, Resolution (logic), Fetus, Computer vision, Anatomy, Pattern recognition (psychology), Radiology, Nuclear medicine, Pregnancy, Computer science, Genetics, Biology

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Cited by: 5

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