Publikationen von G Lohmann

Meyer, M.; Alter, K.; Friederici, A.; Lohmann, G.; von Cramon, D.: FMRI reveals brain regions mediating slow prosodic modulations in spoken sentences. Human Brain Mapping 17 (2), S. 73 - 88 (2002)

Lohmann, G.; Bohn, S.: Using replicator dynamics for analyzing fMRI data of the human brain. IEEE Transactions on Medical Imaging 21 (5), S. 485 - 492 (2002)

Lohmann, G.; Müller, K.; Bosch, V.; Mentzel, H.; Hessler, S.; Chen, L.; Zysset, S.; von Cramon, D.: LIPSIA: a new software system for the evaluation of functional magnetic resonance images of the human brain. Computerized Medical Imaging and Graphics 25 (6), S. 449 - 457 (2001)

Müller, K.; Lohmann, G.; Bosch, V.; von Cramon, D.: On multivariate spectral analysis of fMRI time series. NeuroImage 14 (2), S. 347 - 356 (2001)

Zysset, S.; Müller, K.; Lohmann, G.; von Cramon, D.: Color-word matching stroop task: Separating interference and response conflict. NeuroImage 13 (1), S. 29 - 36 (2001)

Lohmann, G.; von Cramon, D.: Automatic labelling of the human cortical surface using sulcal basins. Medical Image Analysis 4 (3), S. 179 - 188 (2000)

Lohmann, G.; von Cramon, D.; Steinmetz, H.: Sulcal variability of twins. Cerebral Cortex 9 (7), S. 754 - 763 (1999)

Lohmann, G.: Extracting line representations of sulcal and gyral patterns in MR images of the human brain. IEEE Transactions on Medical Imaging 17 (6), S. 1040 - 1048 (1998)

Lohmann, G.: Analysis and synthesis of textures: A co-occurrence-based approach. Computers and Graphics 19 (1), S. 29 - 36 (1995)

Lohmann, G.; Suzuki, H.; Kōgakkai, S.: 3 Jigen Gazo Shori. Bondejitaru, Tokyo, Japan (2009), 243 S.

Lohmann, G.: Volumetric image analysis. Wiley Teubner, Chichester, UK (1998), 243 S.

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)

Lohmann, G.; Stelzer, J.; Zuber, V.; Buschmann, T.; Erb, M.; Scheffler, K.: Correlation bundle statistics in fMRI data. In: 4th International Workshop on Pattern Recognition in Neuroimaging (PRNI 2014). 4th International Workshop on Pattern Recognition in Neuroimaging (PRNI 2014), Tübingen, Germany, 04. Juni 2014 - 06. Juni 2014. IEEE, Piscataway, NJ, USA (2014)

Lohmann, G.; Neumann, J.; Müller, K.; Lepsien, J.: The multiple comparison problem in fMRI a new method based on anatomical priors. In: First MICCAI Workshop on Analysis of Functional Medical Images, S. 1 - 8. First MICCAI Workshop on Analysis of Functional Medical Images, New York, NY, USA, 10. September 2008. (2008)

Lohmann, G.; von Cramon, D.; Colchester, A.: Investigating cortical variability using a generic gyral model. In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006: 9th International Conference, Copenhagen, Denmark, October 1-6, 2006, S. 109 - 116 (Hg. Larsen, R.; Nielsen, M.; Sporring, J.). 9th International Conference on Computing and Computer-Assisted Intervention (MICCAI 2006), Copenhagen, Denmark, 01. Oktober 2006 - 06. Oktober 2006. Springer, Berlin, Germany (2006)

Lohmann, G.; von Cramon, D.; Colchester, A.: A construction of an averaged representation of human cortical gyri using non-linear principal component analysis. In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005: 8th International Conference, Palm Springs, CA, USA, October 26-29, 2005, S. 749 - 756 (Hg. Duncan, J.; Gerig, G.). 8th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2005), Palm Springs, CA, USA, 26. Oktober 2005 - 29. Oktober 2005. Springer, Berlin, Germany (2005)