2 citations · 2 across the 4 of their papers we have counts for
4 papers
Rethinking Annotator Simulation: Realistic Evaluation of Whole-Body PET Lesion Interactive Segmentation Methods
Zdravko Marinov, Moon Kim, Jens Kleesiek +1
Interactive segmentation plays a crucial role in accelerating the annotation, particularly in domains requiring specialized expertise such as nuclear medicine. For example, annotat…
Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained Environments
Calvin Tanama, Kunyu Peng, Zdravko Marinov +2
Deep learning-based models are at the forefront of most driver observation benchmarks due to their remarkable accuracies but are also associated with high computational costs. This…
AutoPET Challenge 2023: Sliding Window-based Optimization of U-Net
Matthias Hadlich, Zdravko Marinov, Rainer Stiefelhagen
Tumor segmentation in medical imaging is crucial and relies on precise delineation. Fluorodeoxyglucose Positron-Emission Tomography (FDG-PET) is widely used in clinical practice to…
Mirror U-Net: Marrying Multimodal Fission with Multi-task Learning for Semantic Segmentation in Medical Imaging
Zdravko Marinov, Simon Reiß, David Kersting +2
Positron Emission Tomography (PET) and Computer Tomography (CT) are routinely used together to detect tumors. PET/CT segmentation models can automate tumor delineation, however, cu…