Cross‐Cohort Automatic Knee MRI Segmentation With Multi‐Planar U‐Nets
Research output: Contribution to journal › Journal article › Research › peer-review
Standard
Cross‐Cohort Automatic Knee MRI Segmentation With Multi‐Planar U‐Nets. / Perslev, Mathias; Pai, Akshay; Runhaar, Jos; Igel, Christian; Dam, Erik B.
In: Journal of Magnetic Resonance Imaging, Vol. 55, No. 2, 2022, p. 1650-1663.Research output: Contribution to journal › Journal article › Research › peer-review
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
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