| Network accelerated motion estimation and reduction (NAMER): convolutional neural network guided retrospective motion correction using a separable motion model MW Haskell, SF Cauley, B Bilgic, J Hossbach, DN Splitthoff, J Pfeuffer, ... Magnetic resonance in medicine 82 (4), 1452-1461, 2019 | 114 | 2019 |
| Sensor-based stroke detection and stroke type classification in table tennis P Blank, J Hoßbach, D Schuldhaus, BM Eskofier Proceedings of the 2015 ACM International Symposium on Wearable Computers …, 2015 | 105 | 2015 |
| Deep learning‐based motion quantification from k‐space for fast model‐based magnetic resonance imaging motion correction J Hossbach, DN Splitthoff, S Cauley, B Clifford, D Polak, WC Lo, H Meyer, ... Medical physics 50 (4), 2148-2161, 2023 | 17 | 2023 |
| Deep OCT angiography image generation for motion artifact suppression J Hossbach, L Husvogt, MF Kraus, JG Fujimoto, AK Maier Bildverarbeitung für die Medizin 2020: Algorithmen–Systeme–Anwendungen …, 2020 | 7 | 2020 |
| Motion guidance lines for robust data consistency–based retrospective motion correction in 2D and 3D MRI D Polak, J Hossbach, DN Splitthoff, B Clifford, WC Lo, A Tabari, M Lang, ... Magnetic Resonance in Medicine 89 (5), 1777-1790, 2023 | 4 | 2023 |
| Deep Neural Networks for Motion Estimation in k-space: Applications and Design J Hossbach, D Splitthoff, M Haskell, S Cauley, H Meyer, J Pfeuffer, ... Proceedings of the Joint Annual Meeting ISMRM-ESMRMB, 4851, 2019 | 3 | 2019 |
| Training a tunable, spatially adaptive denoiser without clean targets L Pfaff, J Hossbach, E Preuhs, T Wuerfl, SA Camejo, MD Nickel, A Maier Proceedings of the joint annual meeting ISMRM-ESMRMB, 2022 | 2 | 2022 |
| Self-supervised MRI denoising: leveraging Stein’s unbiased risk estimator and spatially resolved noise maps L Pfaff, J Hossbach, E Preuhs, F Wagner, S Arroyo Camejo, ... Scientific Reports 13 (1), 22629, 2023 | | 2023 |
| Robust Multi-Contrast Mri Denoising Using Trainable Bilateral Filters Without Noise-Free Targets L Pfaff, F Wagner, J Hossbach, E Preuhs, N Maul, M Thies, F Denzinger, ... 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 1-5, 2023 | | 2023 |
| Coil mixing error matrix and deep learning for prospective motion assessment DN Splitthoff, J Hossbach, D Polak, SF Cauley, B Clifford, WC Lo US Patent 11,630,177, 2023 | | 2023 |
| Computer implemented method and system for magnetic resonance imaging DN Splitthoff, J Hossbach, J Pfeuffer, SF Cauley, M Haskell US Patent 11,187,769, 2021 | | 2021 |
| Post processing and displaying a three-dimensional angiography image data set J Hossbach, R Schneider, P Speier US Patent 10,979,697, 2021 | | 2021 |
| Think outside the box: Exploiting the imaging workflow for Deep Learning based motion estimation and correction J Hossbach, DN Splitthoff, B Clifford, D Polak, WC Lo, S Cauley, A Maier | | |
| Prospective motion assessment within multi-shot imaging using coil mixing of the data consistency error and deep learning J Hossbach, DN Splitthoff, B Clifford, D Polak, SF Cauley, A Maier | | |
| MoPED: Motion Parameter Estimation DenseNet for accelerating retrospective motion correction J Hossbach, DN Splitthoff, SF Cauley, A Maier | | |
| Network Accelerated Motion Estimation and Reduction (NAMER): Accelerating forward model based retrospective motion correction using a convolutional neural network MW Haskell, SF Cauley, B Bilgic, J Hossbach, J Pfeuffer, K Setsompop, ... | | |
Melissa W. HaskellSenior Scientist at HyperfineBestätigte E-Mail-Adresse bei hyperfine.io
