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[HTML][HTML] The role of machine learning and design of experiments in the advancement of biomaterial and tissue engineering research
Optimisation of tissue engineering (TE) processes requires models that can identify
relationships between the parameters to be optimised and predict structural and …
relationships between the parameters to be optimised and predict structural and …
Imaging challenges in biomaterials and tissue engineering
Biomaterials are employed in the fields of tissue engineering and regenerative medicine
(TERM) in order to enhance the regeneration or replacement of tissue function and/or …
(TERM) in order to enhance the regeneration or replacement of tissue function and/or …
Early T2 changes predict onset of radiographic knee osteoarthritis: data from the osteoarthritis initiative
H Liebl, G Joseph, MC Nevitt, N Singh… - Annals of the rheumatic …, 2015 - Elsevier
Objective To evaluate whether T2 relaxation time measurements obtained at 3 T MRI predict
the onset of radiographic knee osteoarthritis (OA). Materials and methods We performed a …
the onset of radiographic knee osteoarthritis (OA). Materials and methods We performed a …
Monitoring cartilage tissue engineering using magnetic resonance spectroscopy, imaging, and elastography
A key technical challenge in cartilage tissue engineering is the development of a
noninvasive method for monitoring the composition, structure, and function of the tissue at …
noninvasive method for monitoring the composition, structure, and function of the tissue at …
Anomalous T2 relaxation in normal and degraded cartilage
Purpose To compare the ordinary monoexponential model with three anomalous relaxation
models—the stretched Mittag‐Leffler, stretched exponential, and biexponential functions …
models—the stretched Mittag‐Leffler, stretched exponential, and biexponential functions …
[HTML][HTML] Machine learning classification of OARSI-scored human articular cartilage using magnetic resonance imaging
Objective The purpose of this study is to evaluate the ability of machine learning to
discriminate between magnetic resonance images (MRI) of normal and pathological human …
discriminate between magnetic resonance images (MRI) of normal and pathological human …
Machine learning prediction of collagen fiber orientation and proteoglycan content from multiparametric quantitative MRI in articular cartilage
SA Mirmojarabian, AW Kajabi… - Journal of Magnetic …, 2023 - Wiley Online Library
Background Machine learning models trained with multiparametric quantitative MRIs
(qMRIs) have the potential to provide valuable information about the structural composition …
(qMRIs) have the potential to provide valuable information about the structural composition …
Vibrational spectroscopy and imaging: applications for tissue engineering
Tissue engineering (TE) approaches strive to regenerate or replace an organ or tissue. The
successful development and subsequent integration of a TE construct is contingent on a …
successful development and subsequent integration of a TE construct is contingent on a …
Incorporation of Rician noise in the analysis of biexponential transverse relaxation in cartilage using a multiple gradient echo sequence at 3 and 7 Tesla
Purpose Previous work has evaluated the quality of different analytic methods for extracting
relaxation times from magnitude imaging data exhibiting Rician noise. However …
relaxation times from magnitude imaging data exhibiting Rician noise. However …
Applications of computer modeling and simulation in cartilage tissue engineering
D Pearce, S Fischer, F Huda, A Vahdati - Tissue Engineering and …, 2020 - Springer
Background: Advances in cartilage tissue engineering have demonstrated noteworthy
potential for develo** cartilage for implantation onto sites impacted by joint degeneration …
potential for develo** cartilage for implantation onto sites impacted by joint degeneration …