ysuter
Postdoc at the University of Bern. Working on medical image analysis of brain tumor MRIs using Deep Learning and machine learning in general.
Pinned Repositories
TAC-GAN_JeHaYaFa
hitobito_pbs
A hitobito wagon defining the organization hierarchy and additional features for Pfadibewegung Schweiz.
Sandbox
New modules created for diffusion MRI tasks in 3D Slicer
MIALab
Medical Image Analysis Lab (MIALab), University of Bern
deepsurvival-baseline
gbm-data-longitudinal
This repository contains code used to prepare the LUMIERE Glioblastoma dataset.
gbm-robustradiomics
Code accompanying the paper "Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques"
OpenBTAI-radiomics
reproducibility-checklist-miccai
Checklist to promote reproducible research for the MICCAI conference. Created during the MICCAI Hackathon 2020.
SlicerDMRI
Diffusion MRI in 3D Slicer open-source medical imaging software
ysuter's Repositories
ysuter/gbm-data-longitudinal
This repository contains code used to prepare the LUMIERE Glioblastoma dataset.
ysuter/gbm-robustradiomics
Code accompanying the paper "Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques"
ysuter/OpenBTAI-radiomics
ysuter/reproducibility-checklist-miccai
Checklist to promote reproducible research for the MICCAI conference. Created during the MICCAI Hackathon 2020.
ysuter/brats20-survivalprediction
This repository contains the code and further information for our contribution to the survival prediction task of the 2020 Brain Tumor Segmentation Challenge (BraTS).
ysuter/gbm-progressionfeatures
This repository will contain the code used for the paper "Towards MRI Progression Features for Glioblastoma Patients: From Automated Volumetry and Classical Radiomics to Deep Feature Learning" by Suter et al., appearing in the proceedings of the 3rd Machine Learning in Clinical Neuroscience Workshop held at MICCAI 2020.
ysuter/MIALab
Medical Image Analysis Lab (MIALab), University of Bern
ysuter/deepsurvival-baseline
ysuter/SlicerDMRI
Diffusion MRI in 3D Slicer open-source medical imaging software
ysuter/bme-labs
ysuter/DeepMedicPlus
Deep learning for brain metastasis detection and segmentation in longitudinal MRI data
ysuter/DeepNeuro
A deep learning python package for neuroimaging data. Made by:
ysuter/doselo
DOSELO (Dose Segmentation Loss Function): Dose Guidance for Radiotherapy-oriented Deep Learning Segmentation
ysuter/GaNDLF
A generalizable application framework for segmentation, regression, and classification using PyTorch
ysuter/gbm-longitudinaleval
ysuter/HD-GLIO-AUTO
Automated processing of MRI in neuro-oncology (combining HD-BET, image co-registration, T1-subtraction mapping and HD-GLIO in one Docker container)
ysuter/hitobito
A web application to manage complex group hierarchies with members, events and a lot more.
ysuter/hitobito_generic
A hitobito wagon defining a basic, generic organization hierarchy.
ysuter/hitobito_pbs
A hitobito wagon defining the organization hierarchy and additional features for Pfadibewegung Schweiz.
ysuter/KLARNet
ysuter/new-modules
New modules created for diffusion MRI tasks in 3D Slicer
ysuter/pymia
pymia: A Python package for data handling and evaluation in deep learning-based medical image analysis
ysuter/pyradiomics
Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks.
ysuter/towardsgbmprogression
ysuter/TrackToLearn
Public release of Track-to-Learn: A general framework for tractography with deep reinforcement learning
ysuter/zukunftstag2023