Felix Steinbauer
A5090098834- Radiomics and Machine Learning in Medical Imaging
- AI in cancer detection
- Mathematical Biology Tumor Growth
- Cell Image Analysis Techniques
- Medical Image Segmentation Techniques
- Generative Adversarial Networks and Image Synthesis
- Medical Imaging Techniques and Applications
Technical University of Munich
2022-2024
A myriad of algorithms for the automatic analysis brain MR images is available to support clinicians in their decision-making. For tumor patients, image acquisition time series typically starts with a scan that already pathological. This poses problems, as many are designed analyze healthy brains and provide no guarantees featuring lesions. Examples include but not limited anatomy parcellation, tissue segmentation, extraction. To solve this dilemma, we introduce BraTS 2023 inpainting...
Current treatment planning of patients diagnosed with a brain tumor, such as glioma, could significantly benefit by accessing the spatial distribution tumor cell concentration. Existing diagnostic modalities, e.g. magnetic resonance imaging (MRI), contrast sufficiently well areas high density. In gliomas, however, they do not portray low concentration, which can often serve source for secondary appearance after treatment. To estimate densities beyond visible boundaries lesion, numerical...