Publikationen von Q Wang

Chen, Y.; Wang, Q.; Choi, S.; Zeng, H.; Takahashi, K.; Qian, C.; Yu, X.: Focal fMRI signal enhancement with implantable inductively coupled detectors. NeuroImage 247, 118793 (2022)

Choi, S.; Takahashi, K.; Jiang, Y.; Köhler, S.; Zeng, H.; Wang, Q.; Ma, Y.; Yu, X.: Real-Time fMRI Brain Mapping in Animals. Journal of Visualized Experiments 2020 (163) (2020)

Wang, Q.; Mahler, L.; Steiglechner, J.; Birk, F.; Scheffler, K.; Lohmann, G.: DISGAN: Wavelet-informed Discriminator Guides GAN to MRI Super-resolution with Noise Cleaning. In: IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, S. 2452 - 2461. 2nd Workshop on Computer Vision for Automated Medical Diagnosis: International Conference on Computer Vision (ICCV/CVF 2023) , Paris, France, 02. Oktober 2023 - 06. Oktober 2023. (2023)

Mahler, L.; Wang, Q.; Steiglechner, J.; Birk, F.; Heczko, S.; Scheffler, K.; Lohmann, G.: Pretraining is All You Need: A Multi-Atlas Enhanced Transformer Framework for Autism Spectrum Disorder Classification. In: Machine Learning in Clinical Neuroimaging: 6th International Workshop, MLCN 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, S. 123 - 132 (Hg. Abdulkadir, A.; Bathula, D.; Dvornek, N.; Govindarajan, S.; Habes, M. et al.). 6th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2023), Vancouver, BC, Canada, 08. Oktober 2023. Springer, Cham, Switzerland (2023)

Wang, Q.; Mahler, L.; Steiglechner, J.; Birk, F.; Scheffler, K.; Lohmann, G.: A Three-Player GAN for Super-Resolution in Magnetic Resonance Imaging. In: Machine Learning in Clinical Neuroimaging: 6th International Workshop, MLCN 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, S. 23 - 33 (Hg. Abdulkadir, A.; Bathula, D.; Dvornek, N.; Govindarajan, S.; Habes, M. et al.). 6th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2023), Vancouver, BC, Canada, 08. Oktober 2023. Springer, Cham, Switzerland (2023)

Steiglechner, J.; Wang, Q.; Ramadan, D.; Mahler, L.; Scheffler, K.; Bender, B.; Lindig, T.; Lohmann, G.: FLEXseg: Next Generation Brain MRI Segmentation at 9.4 T. In: Medical Imaging with Deep Learning (MIDL 2022). Medical Imaging with Deep Learning (MIDL 2022), Zürich, Swtzerland, 06. Juli 2022 - 08. Juli 2022. (2022)

Wang, Q.; Steiglechner, J.; Lindig, T.; Bender, B.; Scheffler, K.; Lohmann, G.: Super-Resolution for Ultra High-Field MR Images. In: Medical Imaging with Deep Learning (MIDL 2022). Medical Imaging with Deep Learning (MIDL 2022) , Zürich, Swtzerland , 06. Juli 2022 - 08. Juli 2022. (2022)

Wang, Q.; Steiglechner, J.; Lohmann, G.: Sythetic 9T-like structural MRI using Generative Neural Network. In NeNa Conference 2021: Neurowissenschaftliche Nachwuchskonferenz (Conference of Junior Neuroscientists), T13, S. 14. 22nd Conference of Junior Neuroscientists (NeNa 2021), Tübingen, Germany, 07. Oktober 2021. (2021)

Chen, Y.; Wang, Q.; Zeng, H.; Takahashi, K.; Choi, S.; Qian, C.; Yu, X.: Inductively coupled detectors for optogenetic-driven focal and multiregional fMRI signal enhancement. In 2021 ISMRM & SMRT Annual Meeting & Exhibition (ISMRM 2021), 0133. 2021 ISMRM & SMRT Annual Meeting & Exhibition (ISMRM 2021), 15. Mai 2021 - 20. Mai 2021. (2021)

Mahler, L.; Steiglechner, J.; Wang, Q.; Scheffler, K.; Lohmann, G.: JudgeMI: Towards Accurate Metrics for Assessing Deep Learning Based Structural MRI Motion Correction. 29th Annual Meeting of the Organization for Human Brain Mapping (OHBM 2023), Montreal, Canada (2023)

Wang, Q.; Steiglechner, J.; Scheffler, K.; Lohmann, G.: Super Resolution Improves Cortical Segmentation Accuracy in Ultra-high Resolution MRI. 28th Annual Meeting of the Organization for Human Brain Mapping (OHBM 2022), Glasgow, UK (2022)

Mahler, L.; Steiglechner, J.; Wang, Q.; Scheffler, K.; Heule, R.: Flexible and Cost-Effective Deep Learning for Fast Multi-Parametric Relaxometry using Phase-Cycled bSSFP. (eingereicht)

Lohmann, G.; Heczko, S.; Mahler, L.; Wang, Q.; Steiglechner, J.; Kumar, V.; Roost, M.; Jost, J.; Scheffler, K.: Improving the reliability of fMRI-based predictions of intelligence via semi-blind machine learning. (eingereicht)