TY - CHAP A1 - Eisenmann, Matthias A1 - Reinke, Annika A1 - Weru, Vivienn A1 - Tizabi, Minu Dietlinde A1 - Isensee, Fabian A1 - Adler, Tim J. A1 - Ali, Sharib A1 - Andrearczyk, Vincent A1 - Aubreville, Marc A1 - Baid, Ujjwal A1 - Bakas, Spyridon A1 - Balu, Niranjan A1 - Bano, Sophia A1 - Bernal, Jorge A1 - Bodenstedt, Sebastian A1 - Casella, Alessandro A1 - Cheplygina, Veronika A1 - Daum, Marie A1 - De Bruijne, Marleen A1 - Depeursinge, Adrien A1 - Dorent, Reuben A1 - Egger, Jan A1 - Ellis, David G. A1 - Engelhardt, Sandy A1 - Ganz, Melanie A1 - Ghatwary, Noha M. A1 - Girard, Gabriel A1 - Godau, Patrick A1 - Gupta, Anubha A1 - Hansen, Lasse A1 - Harada, Kanako A1 - Heinrich, Mattias A1 - Heller, Nicholas A1 - Hering, Alessa A1 - Huaulmé, Arnoud A1 - Jannin, Pierre A1 - Kavur, A. Emre A1 - Kodym, Oldrich A1 - Kozubek, Michal A1 - Li, Jianning A1 - Li, Hongwei A1 - Ma, Jun A1 - Martín-Isla, Carlos A1 - Menze, Bjoern H. A1 - Noble, Alison A1 - Oreiller, Valentin A1 - Padoy, Nicolas A1 - Pati, Sarthak A1 - Payette, Kelly A1 - Rädsch, Tim A1 - Rafael-Patiño, Jonathan A1 - Bawa, Vivek Singh A1 - Speidel, Stefanie A1 - Sudre, Carole H. A1 - Van Wijnen, Kimberlin M. H. A1 - Wagner, M. A1 - Wei, D. A1 - Yamlahi, Amine A1 - Yap, Moi Hoon A1 - Yuan, C. A1 - Zenk, Maximilian A1 - Zia, A. A1 - Zimmerer, David A1 - Aydogan, Dogu Baran A1 - Bhattarai, B. A1 - Bloch, Louise A1 - Brüngel, Raphael A1 - Cho, J. A1 - Choi, C. A1 - Dou, Q. A1 - Ezhov, Ivan A1 - Friedrich, Christoph M. A1 - Fuller, C. A1 - Gaire, Rebati Raman A1 - Galdran, Adrian A1 - García-Faura, Álvaro A1 - Grammatikopoulou, Maria A1 - Hong, S. A1 - Jahanifar, Mostafa A1 - Jang, I. A1 - Kadkhodamohammadi, Abdolrahim A1 - Kang, I. A1 - Kofler, Florian A1 - Kondo, Satoshi A1 - Kuijf, Hugo Jaco A1 - Li, M. A1 - Luu, M. A1 - Martinčič, Tomaz A1 - Morais, P. A1 - Naser, M. A. A1 - Oliveira, B. A1 - Owen, D. A1 - Pang, S. A1 - Park, Jinah A1 - Park, S. A1 - Płotka, S. A1 - Puybareau, Élodie A1 - Rajpoot, Nasir M. A1 - Ryu, K. A1 - Saeed, N. A1 - Shephard, Adam A1 - Shi, P. A1 - Štepec, Dejan A1 - Subedi, Ronast A1 - Tochon, Guillaume A1 - Torres, Helena R. A1 - Urien, Hélène A1 - Vilaça, João L. A1 - Wahid, Kareem A. A1 - Wang, H. A1 - Wang, J. A1 - Wang, L. A1 - Wang, Xiyue A1 - Wiestler, Benedikt A1 - Wodzinski, Marek A1 - Xia, F. A1 - Xie, J. A1 - Xiong, Z. A1 - Yang, Sen A1 - Yang, Y. A1 - Zhao, Z. A1 - Maier-Hein, Klaus H. A1 - Jäger, Paul F. A1 - Kopp-Schneider, Annette A1 - Maier-Hein, Lena T1 - Why is the Winner the Best? T2 - Proceedings: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition UR - https://doi.org/10.1109/CVPR52729.2023.01911 KW - Medical and biological vision KW - cell microscopy Y1 - 2023 UR - https://doi.org/10.1109/CVPR52729.2023.01911 SN - 979-8-3503-0129-8 SN - 2575-7075 SP - 19955 EP - 19967 PB - IEEE CY - Los Alamitos ER - TY - JOUR A1 - Pirkl, Carolin A1 - Cencini, Matteo A1 - Kurzawski, Jan W. A1 - Waldmannstetter, Diana A1 - Li, Hongwei A1 - Menzel, Marion Irene T1 - Learning residual motion correction for fast and robust 3D multiparametric MRI JF - Medical Image Analysis N2 - Voluntary and involuntary patient motion is a major problem for data quality in clinical routine of Magnetic Resonance Imaging (MRI). It has been thoroughly investigated and, yet it still remains unresolved. In quantitative MRI, motion artifacts impair the entire temporal evolution of the magnetization and cause errors in parameter estimation. Here, we present a novel strategy based on residual learning for retrospective motion correction in fast 3D whole-brain multiparametric MRI. We propose a 3D multiscale convolutional neural network (CNN) that learns the non-linear relationship between the motion-affected quantitative parameter maps and the residual error to their motion-free reference. For supervised model training, despite limited data availability, we propose a physics-informed simulation to generate self-contained paired datasets from a priori motion-free data. We evaluate motion-correction performance of the proposed method for the example of 3D Quantitative Transient-state Imaging at 1.5T and 3T. We show the robustness of the motion correction for various motion regimes and demonstrate the generalization capabilities of the residual CNN in terms of real-motion in vivo data of healthy volunteers and clinical patient cases, including pediatric and adult patients with large brain lesions. Our study demonstrates that the proposed motion correction outperforms current state of the art, reliably providing a high, clinically relevant image quality for mild to pronounced patient movements. This has important implications in clinical setups where large amounts of motion affected data must be discarded as they are rendered diagnostically unusable. UR - https://doi.org/10.1016/j.media.2022.102387 KW - Multiparametric MRI KW - 3D Motion correction KW - Residual learning KW - Multiscale CNN Y1 - 2022 UR - https://doi.org/10.1016/j.media.2022.102387 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-13861 SN - 1361-8423 VL - 2022 IS - 77 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Pirkl, Carolin A1 - Cencini, Matteo A1 - Kurzawski, Jan W. A1 - Waldmannstetter, Diana A1 - Li, Hongwei A1 - Sekuboyina, Anjany A1 - Endt, Sebastian A1 - Peretti, Luca A1 - Donatelli, Graziella A1 - Pasquariello, Rosa A1 - Costagli, Mauro A1 - Buonincontri, Guido A1 - Tosetti, Michela A1 - Menzel, Marion Irene A1 - Menze, Bjoern H. T1 - Residual learning for 3D motion corrected quantitative MRI BT - Robust clinical T1, T2 and proton density mapping T2 - Medical Imaging with Deep Learning MIDL 2021 KW - 3D multiparametric MRI KW - motion correction KW - deep learning KW - residual learning KW - multiscale CNN Y1 - 2021 UR - https://openreview.net/forum?id=hxgQM71AuRA PB - OpenReview ER - TY - CHAP A1 - Pirkl, Carolin A1 - Cencini, Matteo A1 - Kurzawski, Jan W. A1 - Waldmannstetter, Diana A1 - Li, Hongwei A1 - Sekuboyina, Anjany A1 - Endt, Sebastian A1 - Peretti, Luca A1 - Donatelli, Graziella A1 - Pasquariello, Rosa A1 - Costagli, Mauro A1 - Buonincontri, Guido A1 - Tosetti, Michela A1 - Menzel, Marion Irene A1 - Menze, Bjoern H. T1 - Residual learning for 3D motion corrected quantitative MRI: Robust clinical T1, T2 and proton density mapping T2 - Proceedings of Machine Learning Research Y1 - 2021 UR - https://proceedings.mlr.press/v143/pirkl21a.html SP - 618 EP - 632 PB - PMLR CY - [s. l.] ER -