Cross‐Cohort Automatic Knee MRI Segmentation With Multi‐Planar U‐Nets
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Cross‐Cohort Automatic Knee MRI Segmentation With Multi‐Planar U‐Nets. / Perslev, Mathias; Pai, Akshay; Runhaar, Jos; Igel, Christian; Dam, Erik B.
I: Journal of Magnetic Resonance Imaging, Bind 55, Nr. 2, 2022, s. 1650-1663.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Cross‐Cohort Automatic Knee MRI Segmentation With Multi‐Planar U‐Nets
AU - Perslev, Mathias
AU - Pai, Akshay
AU - Runhaar, Jos
AU - Igel, Christian
AU - Dam, Erik B.
PY - 2022
Y1 - 2022
N2 - BackgroundSegmentation of medical image volumes is a time-consuming manual task. Automatic tools are often tailored toward specific patient cohorts, and it is unclear how they behave in other clinical settings.PurposeTo evaluate the performance of the open-source Multi-Planar U-Net (MPUnet), the validated Knee Imaging Quantification (KIQ) framework, and a state-of-the-art two-dimensional (2D) U-Net architecture on three clinical cohorts without extensive adaptation of the algorithms.
AB - BackgroundSegmentation of medical image volumes is a time-consuming manual task. Automatic tools are often tailored toward specific patient cohorts, and it is unclear how they behave in other clinical settings.PurposeTo evaluate the performance of the open-source Multi-Planar U-Net (MPUnet), the validated Knee Imaging Quantification (KIQ) framework, and a state-of-the-art two-dimensional (2D) U-Net architecture on three clinical cohorts without extensive adaptation of the algorithms.
UR - https://doi.org/10.1002/jmri.27978
U2 - 10.1002/jmri.27978
DO - 10.1002/jmri.27978
M3 - Journal article
C2 - 34918423
VL - 55
SP - 1650
EP - 1663
JO - Journal of Magnetic Resonance Imaging
JF - Journal of Magnetic Resonance Imaging
SN - 1053-1807
IS - 2
ER -
ID: 287687378