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Roland Opfer

Showing results (11-20 of 33) with videos related to

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Physics in Medicine and Biology|November 13, 2013
Fully automatic detection of deep white matter T1 hypointense lesions in multiple sclerosisLothar Spies, Anja Tewes, Per Suppa, et al.
International Journal of Computer Assisted Radiology and Surgery|June 16, 2024
BrainLossNet: a fast, accurate and robust method to estimate brain volume loss from longitudinal MRIRoland Opfer, Julia Krüger, Thomas Buddenkotte, et al.
Nuklearmedizin. Nuclear Medicine|June 24, 2026
On the utility of ChatGPT in conducting a literature review on deep learning for dopamine transporter SPECT with [¹²³I]ioflupaneThomas Buddenkotte, Ivayla Ilieva Apostolova, Roland Opfer, et al.
Computers in Biology and Medicine|October 18, 2024
Higher effect sizes for the detection of accelerated brain volume loss and disability progression in multiple sclerosis using deep-learningRoland Opfer, Tjalf Ziemssen, Julia Krüger, et al.
European Radiology|October 20, 2022
Automatic segmentation of the thalamus using a massively trained 3D convolutional neural network: higher sensitivity for the detection of reduced thalamus volume by improved inter-scanner stabilityRoland Opfer, Julia Krüger, Lothar Spies, et al.
Neuroimage. Clinical|December 27, 2016
MRI FLAIR lesion segmentation in multiple sclerosis: Does automated segmentation hold up with manual annotation?Christine Egger, Roland Opfer, Chenyu Wang, et al.
European Radiology|October 13, 2021
Infratentorial lesions in multiple sclerosis patients: intra- and inter-rater variability in comparison to a fully automated segmentation using 3D convolutional neural networksJulia Krüger, Ann-Christin Ostwaldt, Lothar Spies, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|August 16, 2020
Multiple sclerosis lesion activity segmentation with attention-guided two-path CNNsNils Gessert, Julia Krüger, Roland Opfer, et al.
Neuroimage. Clinical|October 10, 2020
Fully automated longitudinal segmentation of new or enlarged multiple sclerosis lesions using 3D convolutional neural networksJulia Krüger, Roland Opfer, Nils Gessert, et al.
Journal of Neurology|March 18, 2018
Within-patient fluctuation of brain volume estimates from short-term repeated MRI measurements using SIENA/FSLRoland Opfer, Ann-Christin Ostwaldt, Christine Walker-Egger, et al.
Pageof 4

Showing results (11-20 of 33) with videos related to

Sort By:
Pageof 4
Physics in Medicine and Biology|November 13, 2013
Fully automatic detection of deep white matter T1 hypointense lesions in multiple sclerosisLothar Spies, Anja Tewes, Per Suppa, et al.
International Journal of Computer Assisted Radiology and Surgery|June 16, 2024
BrainLossNet: a fast, accurate and robust method to estimate brain volume loss from longitudinal MRIRoland Opfer, Julia Krüger, Thomas Buddenkotte, et al.
Nuklearmedizin. Nuclear Medicine|June 24, 2026
On the utility of ChatGPT in conducting a literature review on deep learning for dopamine transporter SPECT with [¹²³I]ioflupaneThomas Buddenkotte, Ivayla Ilieva Apostolova, Roland Opfer, et al.
Computers in Biology and Medicine|October 18, 2024
Higher effect sizes for the detection of accelerated brain volume loss and disability progression in multiple sclerosis using deep-learningRoland Opfer, Tjalf Ziemssen, Julia Krüger, et al.
European Radiology|October 20, 2022
Automatic segmentation of the thalamus using a massively trained 3D convolutional neural network: higher sensitivity for the detection of reduced thalamus volume by improved inter-scanner stabilityRoland Opfer, Julia Krüger, Lothar Spies, et al.
Neuroimage. Clinical|December 27, 2016
MRI FLAIR lesion segmentation in multiple sclerosis: Does automated segmentation hold up with manual annotation?Christine Egger, Roland Opfer, Chenyu Wang, et al.
European Radiology|October 13, 2021
Infratentorial lesions in multiple sclerosis patients: intra- and inter-rater variability in comparison to a fully automated segmentation using 3D convolutional neural networksJulia Krüger, Ann-Christin Ostwaldt, Lothar Spies, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|August 16, 2020
Multiple sclerosis lesion activity segmentation with attention-guided two-path CNNsNils Gessert, Julia Krüger, Roland Opfer, et al.
Neuroimage. Clinical|October 10, 2020
Fully automated longitudinal segmentation of new or enlarged multiple sclerosis lesions using 3D convolutional neural networksJulia Krüger, Roland Opfer, Nils Gessert, et al.
Journal of Neurology|March 18, 2018
Within-patient fluctuation of brain volume estimates from short-term repeated MRI measurements using SIENA/FSLRoland Opfer, Ann-Christin Ostwaldt, Christine Walker-Egger, et al.
Pageof 4