Publications (7)
The use of deep learning in interventional radiotherapy (brachytherapy): a review with a focus on open source and open data
Tobias Fechter, Ilias Sachpazidis, Dimos Baltas
Deep learning advanced to one of the most important technologies in almost all medical fields. Especially in areas, related to medical imaging it plays a big role. However, in inte…
Measuring breathing induced oesophageal motion and its dosimetric impact
Tobias Fechter, Sonja Adebahr, Anca-Ligia Grosu +1
Stereotactic body radiation therapy allows for a precise and accurate dose delivery. Organ motion during treatment bears the risk of undetected high dose healthy tissue exposure. A…
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…
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…
Prediction of Local Failure after Stereotactic Radiotherapy in Melanoma Brain Metastases Using Ensemble Learning on Clinical, Dosimetric, and Radiomic Data
Nanna E. Hartong, Ilias Sachpazidis, Oliver Blanck +9
Background: This study aimed to predict lesion-specific outcomes after stereotactic radiotherapy (SRT) in patients with brain metastases from malignant melanoma (MBM), using clinic…
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…