7 citations · 15 across the 10 of their papers we have counts for
4 papers · 1 filter
Deep-Learning Atlas Registration for Melanoma Brain Metastases: Preserving Pathology While Enabling Cohort-Level Analyses
Nanna E. Wielenberg, Ilinca Popp, Oliver Blanck +6
Melanoma brain metastases (MBM) are common and spatially heterogeneous lesions, complicating cohort-level analyses due to anatomical variability and differing MRI protocols. We pro…
Convolutional neural network based deep-learning architecture for intraprostatic tumour contouring on PSMA PET images in patients with primary prostate cancer
Dejan Kostyszyn, Tobias Fechter, Nico Bartl +22
Accurate delineation of the intraprostatic gross tumour volume (GTV) is a prerequisite for treatment approaches in patients with primary prostate cancer (PCa). Prostate-specific me…
One Shot Learning for Deformable Medical Image Registration and Periodic Motion Tracking
Tobias Fechter, Dimos Baltas
Deformable image registration is a very important field of research in medical imaging. Recently multiple deep learning approaches were published in this area showing promising res…
A 3D fully convolutional neural network and a random walker to segment the esophagus in CT
Tobias Fechter, Sonja Adebahr, Dimos Baltas +3
Precise delineation of organs at risk (OAR) is a crucial task in radiotherapy treatment planning, which aims at delivering high dose to the tumour while sparing healthy tissues. In…