AssländerJMaoABeckES, et al. On multi-path longitudinal spin relaxation in brain tissue. arXiv:2301.08394v1; 2023. Available at: https://arxiv.org/pdf/2301.08394.pdf. Accessed July 29, 2023.
2.
Baker-LePainJCLynchJAParimiN, et al. Variant alleles of the WNT antagonist FRZB are determinants of hip shape and modify the relationship between hip shape and osteoarthritis. Arthritis Rheum. 2012;64(5):1457–1465.
3.
BencikovaDCloosMAJanacovaVTrattnigSJurasV.Magnetic resonance fingerprinting in the knee cartilage compared to conventional methods using automated cartilage segmentation. Osteoarthritis Cartilage. 2023;31:S284–S285.
4.
Ben-EliezerNSodicksonDKBlockKT.Rapid and accurate T2 mapping from multi-spin-echo data using Bloch-simulation-based reconstruction. Magn Reson Med. 2015;73(2):809–817.
5.
CloosMAAssländerJAbbasB, et al. Rapid radial T1 and T2 mapping of the hip articular cartilage with magnetic resonance fingerprinting. J Magn Reson Imaging. 2019;50(3):810–815.
6.
FernquestSParkDMarcanMPalmerAVoiculescuIGlyn-JonesS.Segmentation of hip cartilage in compositional magnetic resonance imaging: a fast, accurate, reproducible, and clinically viable semi-automated methodology. J Orthop Res. 2018;36:2280–2287.
7.
GirardMPedoiaVNormanBRossi-DevriesJMajumdarS.Automatic segmentation of hip cartilage with deep convolutional neural nets for the evaluation of acetabulum and femoral T1ρ and T2 relaxation times. Osteoarthritis Cartilage. 2018;26:S439–S440.
8.
LattanziRPetchprapaCAscaniD, et al. Detection of cartilage damage in femoroacetabular impingement with standardized dGEMRIC at 3 T. Osteoarthritis Cartilage. 2014;22(3):447–456.
9.
LattanziRPetchprapaCGlaserC, et al. A new method to analyze dGEMRIC measurements in femoroacetabular impingement: preliminary validation against arthroscopic findings. Osteoarthritis Cartilage. 2012;20(10):1127–1133.
10.
LiaoTPedoiaVNeumannJLinkTMSouzaRBMajumdarS.Extracting voxel-based cartilage relaxometry features in hip osteoarthritis subjects using principal component analysis. J Magn Reson Imaging. 2020;51(6):1708–1719.
11.
MaDGulaniVSeiberlichN, et al. Magnetic resonance fingerprinting. Nature. 2013;495(7440):187–192.
12.
McCarthyJCJarrettBTOjeifoOLeeJABragdonCR.What factors influence long-term survivorship after hip arthroscopy?Clin Orthop Relat Res. 2011;469(2):362–371.
13.
MirmojarabianSAKajabiAWKetolaJHJ, et al. Machine learning prediction of collagen fiber orientation and proteoglycan content from multiparametric quantitative MRI in articular cartilage. J Magn Reson Imaging. 2022;57(4):1056–1068.
14.
MontinEKijowskiRYoumTLattanziRA.A radiomics approach to the diagnosis of femoroacetabular impingement. Front Radiol. 2023;3:1151258.
15.
NeogiTBowesMANiuJ, et al. Magnetic resonance imaging–based three-dimensional bone shape of the knee predicts onset of knee osteoarthritis: data from the osteoarthritis initiative. Arthritis Rheum. 2013;65(8):2048–2058.
16.
NormanBPedoiaVMajumdarS.Use of 2D u-net convolutional neural networks for automated cartilage and meniscus segmentation of knee MR imaging data to determine relaxometry and morphometry. Radiology. 2018;288(1):177–185.
17.
PedoiaVGalloMCSouzaRBMajumdarS.Longitudinal study using voxel-based relaxometry: association between cartilage T1ρ and T2 and patient reported outcome changes in hip osteoarthritis. J Magn Reson Imaging. 2017;45(5):1523–1533.
18.
PedoiaVLiXSuFCalixtoNMajumdarS.Fully automatic analysis of the knee articular cartilage T1ρ relaxation time using voxel-based relaxometry. J Magn Reson Imaging. 2016;43(4):970–980.
19.
PetchprapaCNDunhamKSLattanziRRechtMP.Demystifying radial imaging of the hip. Radiographics. 2013;33(3):E97–E112.
20.
RayaJGDietrichOHorngAWeberJReiserMFGlaserC.T2 measurement in articular cartilage: impact of the fitting method on accuracy and precision at low SNR. Magn Reson Med. 2010;63(1):181–193.
21.
RileyGMMcWalterEJStevensKJSafranMRLattanziRGoldGE.MRI of the hip for the evaluation of femoroacetabular impingement: past, present, and future. J Magn Reson Imaging. 2015;41(3):558–572.
22.
Rossi-deVriesJPedoiaVSamaanMAFergusonARSouzaRBMajumdarS.Using multidimensional topological data analysis to identify traits of hip osteoarthritis. J Magn Reson Imaging. 2018;48(4):1046–1058.
23.
SamaanMAPedoiaVZhangAL, et al. A novel MR-based method for detection of cartilage delamination in femoroacetabular impingement patients. J Orthop Res. 2018;36(4):971–978.
24.
SharafiAZibettiMVWChangGCloosMARegatteRR.MR fingerprinting for rapid simultaneous T1, T2, and T1ρ relaxation mapping of the human articular cartilage at 3T. Magn Reson Med. 2020;84(5):2636–2644.
25.
SharafiAZibettiMVWChangGCloosMARegatteRR.Simultaneous bilateral T1, T2, and T1ρ relaxation mapping of the hip joint with magnetic resonance fingerprinting. NMR Biomed. 2022;35(5):e4651.
26.
XiaYChandraSSEngstromCStrudwickMWCrozierSFrippJ.Automatic hip cartilage segmentation from 3D MR images using arc-weighted graph searching. Phys Med Biol. 2014;59(23):7245–7266.
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