A method for comparing MRI sequences of the knee for segmentation based on morphological features

The ultimate goal of this study is to present a methodology for selecting the most appropriate MRI sequence for segmentation, which can be applied to images of other parts in addition to the knee images used in the study. The method we present quantitatively evaluates the edge characteristics, and experimental results show that our method shows consistent results according to the edge. Our method will provide additional information for MRI sequence selection for segmentation.

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Institutions

Publication Details

Journal
PLoS ONE
Published
2024-12-27
DOI
https://doi.org/10.1371/journal.pone.0311532
Citations
2
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.81

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article

A method for comparing MRI sequences of the knee for segmentation based on morphological features

Michael Skipper Andersen, Morten Bilde Simonsen, Yunsub Jung
2 citations
PLoS ONE
Radiomics and Machine Learning in Medical Imaging
0.81
article

A method for comparing MRI sequences of the knee for segmentation based on morphological features

Michael Skipper Andersen, Morten Bilde Simonsen, Yunsub Jung
article en
2 citations

Abstract

The ultimate goal of this study is to present a methodology for selecting the most appropriate MRI sequence for segmentation, which can be applied to images of other parts in addition to the knee images used in the study. The method we present quantitatively evaluates the edge characteristics, and experimental results show that our method shows consistent results according to the edge. Our method will provide additional information for MRI sequence selection for segmentation.

PLoS ONEVol. 19(12)
Aalborg University (DK)
Novo Nordisk, Novo Nordisk Fonden
Openalex Percentile: Top 24%
Radiomics and Machine Learning in Medical Imaging
0.81
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