PHIMO - Physics-Informed Deep Learning for Motion-Corrected Reconstruction of Quantitative Brain MRI

doi:doi:10.57702/obryb3ro

PHIMO - Physics-Informed Deep Learning for Motion-Corrected Reconstruction of Quantitative Brain MRI

PHIMO, a physics-informed motion correction method tailored to quantitative MRI, which utilises information from the MR signal evolution to detect motion events with a subject-specific, self-supervised MLP.

BibTex:

@dataset{Hannah_Eichhorn_and_Veronika_Spieker_and_Kerstin_Hammernik_and_Elisa_Saks_and_Kilian_Weiss_and_Christine_Preibisch_and_Julia_A_Schnabel_2024,
    abstract = {PHIMO, a physics-informed motion correction method tailored to quantitative MRI, which utilises information from the MR signal evolution to detect motion events with a subject-specific, self-supervised MLP.},
    author = {Hannah Eichhorn and Veronika Spieker and Kerstin Hammernik and Elisa Saks and Kilian Weiss and Christine Preibisch and Julia A. Schnabel},
    doi = {10.57702/obryb3ro},
    institution = {No Organization},
    keyword = {'motion correction', 'physics-informed learning', 'quantitative MRI', 'self-supervised learning'},
    month = {dec},
    publisher = {TIB},
    title = {PHIMO - Physics-Informed Deep Learning for Motion-Corrected Reconstruction of Quantitative Brain MRI},
    url = {https://service.tib.eu/ldmservice/dataset/phimo---physics-informed-deep-learning-for-motion-corrected-reconstruction-of-quantitative-brain-mri},
    year = {2024}
}