| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 1906 | 2018 |
| Ntire 2020 challenge on spectral reconstruction from an rgb image B Arad, R Timofte, O Ben-Shahar, YT Lin, GD Finlayson Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 235 | 2020 |
| Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms CMW Tax, F Grussu, E Kaden, L Ning, U Rudrapatna, CJ Evans, ... NeuroImage 195, 285-299, 2019 | 108 | 2019 |
| Segmentation of brain tumors and patient survival prediction: Methods for the brats 2018 challenge L Weninger, O Rippel, S Koppers, D Merhof Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019 | 95 | 2019 |
| Reconstructing spectral images from rgb-images using a convolutional neural network T Stiebel, S Koppers, P Seltsam, D Merhof Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 72 | 2018 |
| Cross-scanner and cross-protocol multi-shell diffusion MRI data harmonization: Algorithms and results L Ning, E Bonet-Carne, F Grussu, F Sepehrband, E Kaden, J Veraart, ... Neuroimage 221, 117128, 2020 | 62 | 2020 |
| Abnormal maturation of the resting‐state peak alpha frequency in children with autism spectrum disorder JC Edgar, M Dipiero, E McBride, HL Green, J Berman, M Ku, S Liu, ... Human Brain Mapping 40 (11), 3288-3298, 2019 | 55 | 2019 |
| Direct estimation of fiber orientations using deep learning in diffusion imaging S Koppers, D Merhof International Workshop on Machine Learning in Medical Imaging, 53-60, 2016 | 53 | 2016 |
| Diffusion MRI signal augmentation: from single shell to multi shell with deep learning S Koppers, C Haarburger, D Merhof Computational Diffusion MRI: MICCAI Workshop, Athens, Greece, October 2016 …, 2017 | 44 | 2017 |
| Spherical harmonic residual network for diffusion signal harmonization S Koppers, L Bloy, JI Berman, CMW Tax, JC Edgar, D Merhof Computational Diffusion MRI: International MICCAI Workshop, Granada, Spain …, 2019 | 34 | 2019 |
| Muti-shell diffusion MRI harmonisation and enhancement challenge (MUSHAC): progress and results L Ning, E Bonet-Carne, F Grussu, F Sepehrband, E Kaden, J Veraart, ... Computational Diffusion MRI: International MICCAI Workshop, Granada, Spain …, 2019 | 20 | 2019 |
| Reconstruction of diffusion anisotropies using 3D deep convolutional neural networks in diffusion imaging S Koppers, M Friedrichs, D Merhof Modeling, analysis, and visualization of anisotropy, 393-404, 2017 | 18 | 2017 |
| 3D fluorescence microscopy data synthesis for segmentation and benchmarking D Eschweiler, M Rethwisch, M Jarchow, S Koppers, J Stegmaier Plos one 16 (12), e0260509, 2021 | 16 | 2021 |
| Spherical harmonics for shape-constrained 3D cell segmentation D Eschweiler, M Rethwisch, S Koppers, J Stegmaier 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 792-796, 2021 | 12 | 2021 |
| Cross-vendor and Cross-protocol harmonisation of diffusion MRI data: a comparative study CMW Tax, F Grussu, E Kaden, L Ning, U Rudrapatna, J Evans, S St-Jean, ... International Symposium on Magnetic Resonance in Medicine (Paris) 471, 2018 | 11 | 2018 |
| Peak alpha frequency and thalamic structure in children with typical development and autism spectrum disorder HL Green, M Dipiero, S Koppers, JI Berman, L Bloy, S Liu, E McBride, ... Journal of autism and developmental disorders 52, 103-112, 2022 | 10 | 2022 |
| Reliable estimation of the number of compartments in diffusion mri S Koppers, C Haarburger, JC Edgar, D Merhof Bildverarbeitung für die Medizin 2017: Algorithmen-Systeme-Anwendungen …, 2017 | 8 | 2017 |
| Free-water correction in diffusion mri: a reliable and robust learning approach L Weninger, S Koppers, CH Na, K Juetten, D Merhof Computational Diffusion MRI: MICCAI Workshop, Shenzhen, China, October 2019 …, 2020 | 7 | 2020 |
| Delimit pytorch-an extension for deep learning in diffusion imaging S Koppers, D Merhof arXiv preprint arXiv:1808.01517, 2018 | 7 | 2018 |
| Sodium image denoising based on a convolutional denoising autoencoder S Koppers, E Coussoux, S Romanzetti, K Reetz, D Merhof Bildverarbeitung für die Medizin 2019: Algorithmen–Systeme–Anwendungen …, 2019 | 5 | 2019 |
