Publications (5)
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas, Mauricio Reyes, Andras Jakab +421
Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritum…
Spherical Harmonics for Shape-Constrained 3D Cell Segmentation
Dennis Eschweiler, Malte Rethwisch, Simon Koppers +1
Recent microscopy imaging techniques allow to precisely analyze cell morphology in 3D image data. To process the vast amount of image data generated by current digitized imaging te…
3D fluorescence microscopy data synthesis for segmentation and benchmarking
Dennis Eschweiler, Malte Rethwisch, Mareike Jarchow +2
Automated image processing approaches are indispensable for many biomedical experiments and help to cope with the increasing amount of microscopy image data in a fast and reproduci…
Spherical Harmonic Residual Network for Diffusion Signal Harmonization
Simon Koppers, Luke Bloy, Jeffrey I. Berman +3
Diffusion imaging is an important method in the field of neuroscience, as it is sensitive to changes within the tissue microstructure of the human brain. However, a major challenge…
DELIMIT PyTorch - An extension for Deep Learning in Diffusion Imaging
Simon Koppers, Dorit Merhof
DELIMIT is a framework extension for deep learning in diffusion imaging, which extends the basic framework PyTorch towards spherical signals. Based on several novel layers, deep le…