Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Pirkl, Carolin"'
Magnetic Resonance Fingerprinting (MRF) is a time-efficient approach to quantitative MRI, enabling the mapping of multiple tissue properties from a single, accelerated scan. However, achieving accurate reconstructions remains challenging, particularl
Externí odkaz:
http://arxiv.org/abs/2410.23318
Autor:
Mayo, Perla, Cencini, Matteo, Pirkl, Carolin M., Menzel, Marion I., Tosetti, Michela, Menze, Bjoern H., Golbabaee, Mohammad
Magnetic Resonance Fingerprinting (MRF) is a time-efficient approach to quantitative MRI for multiparametric tissue mapping. The reconstruction of quantitative maps requires tailored algorithms for removing aliasing artefacts from the compressed samp
Externí odkaz:
http://arxiv.org/abs/2408.02367
Autor:
Mayo, Perla, Cencini, Matteo, Fatania, Ketan, Pirkl, Carolin M., Menzel, Marion I., Menze, Bjoern H., Tosetti, Michela, Golbabaee, Mohammad
The estimation of multi-parametric quantitative maps from Magnetic Resonance Fingerprinting (MRF) compressed sampled acquisitions, albeit successful, remains a challenge due to the high underspampling rate and artifacts naturally occuring during imag
Externí odkaz:
http://arxiv.org/abs/2407.19866
Autor:
Fuderer, Miha, Wichtmann, Barbara, Crameri, Fabio, deSouza, Nandita M., Baeßler, Bettina, Gulani, Vikas, Wang, Meiyun, Poot, Dirk, de Boer, Ruud, Cashmore, Matt, de Graaf, Wolter, Keenan, Kathryn E., Ma, Dan, Pirkl, Carolin, Sollmann, Nico, Weingärtner, Sebastian, Mandija, Stefano, Golay, Xavier
Purpose: To harmonize the use of color for MR relaxometry maps and therefore recommend the use of specific color-maps for representing T1 and T2 maps. Methods: Perceptually linearized color-maps were chosen to have similar color settings as those pro
Externí odkaz:
http://arxiv.org/abs/2407.03906
Autor:
Fatania, Ketan, Chau, Kwai Y., Pirkl, Carolin M., Menzel, Marion I., Hall, Peter, Golbabaee, Mohammad
Current state-of-the-art reconstruction for quantitative tissue maps from fast, compressive, Magnetic Resonance Fingerprinting (MRF), use supervised deep learning, with the drawback of requiring high-fidelity ground truth tissue map training data whi
Externí odkaz:
http://arxiv.org/abs/2211.12786
Autor:
Kaushik, Sandeep, Bylund, Mikael, Cozzini, Cristina, Shanbhag, Dattesh, Petit, Steven F, Wyatt, Jonathan J, Menzel, Marion I, Pirkl, Carolin, Mehta, Bhairav, Chauhan, Vikas, Chandrasekharan, Kesavadas, Jonsson, Joakim, Nyholm, Tufve, Wiesinger, Florian, Menze, Bjoern
In this work, we present a method for synthetic CT (sCT) generation from zero-echo-time (ZTE) MRI aimed at structural and quantitative accuracies of the image, with a particular focus on the accurate bone density value prediction. We propose a loss f
Externí odkaz:
http://arxiv.org/abs/2203.16288
Current spatiotemporal deep learning approaches to Magnetic Resonance Fingerprinting (MRF) build artefact-removal models customised to a particular k-space subsampling pattern which is used for fast (compressed) acquisition. This may not be useful wh
Externí odkaz:
http://arxiv.org/abs/2202.05269
Autor:
Pirkl, Carolin M., Gómez, Pedro A., Lipp, Ilona, Buonincontri, Guido, Molina-Romero, Miguel, Sekuboyina, Anjany, Waldmannstetter, Diana, Dannenberg, Jonathan, Endt, Sebastian, Merola, Alberto, Whittaker, Joseph R., Tomassini, Valentina, Tosetti, Michela, Jones, Derek K., Menze, Bjoern H., Menzel, Marion I.
Magnetic Resonance Fingerprinting (MRF) enables the simultaneous quantification of multiple properties of biological tissues. It relies on a pseudo-random acquisition and the matching of acquired signal evolutions to a precomputed dictionary. However
Externí odkaz:
http://arxiv.org/abs/2005.02020
Autor:
Golbabaee, Mohammad, Buonincontri, Guido, Pirkl, Carolin, Menzel, Marion, Menze, Bjoern, Davies, Mike, Gomez, Pedro
We propose a dictionary-matching-free pipeline for multi-parametric quantitative MRI image computing. Our approach has two stages based on compressed sensing reconstruction and deep learned quantitative inference. The reconstruction phase is convex a
Externí odkaz:
http://arxiv.org/abs/2001.08746
Autor:
Gómez, Pedro A., Cencini, Matteo, Golbabaee, Mohammad, Schulte, Rolf F., Pirkl, Carolin, Horvath, Izabela, Fallo, Giada, Peretti, Luca, Tosetti, Michela, Menze, Bjoern H., Buonincontri, Guido
Novel methods for quantitative, transient-state multiparametric imaging are increasingly being demonstrated for assessment of disease and treatment efficacy. Here, we build on these by assessing the most common Non-Cartesian readout trajectories (2D/
Externí odkaz:
http://arxiv.org/abs/2001.07173