4 papers
CBCTLiTS: A Synthetic, Paired CBCT/CT Dataset For Segmentation And Style Transfer
Maximilian E. Tschuchnig, Philipp Steininger, Michael Gadermayr
Medical imaging is vital in computer assisted intervention. Particularly cone beam computed tomography (CBCT) with defacto real time and mobility capabilities plays an important ro…
Virtually Objective Quantification of in vitro Wound Healing Scratch Assays with the Segment Anything Model
Katja Löwenstein, Johanna Rehrl, Anja Schuster +1
The in vitro scratch assay is a widely used assay in cell biology to assess the rate of wound closure related to a variety of therapeutic interventions. While manual measurement is…
Multimodal Learning With Intraoperative CBCT & Variably Aligned Preoperative CT Data To Improve Segmentation
Maximilian E. Tschuchnig, Philipp Steininger, Michael Gadermayr
Cone-beam computed tomography (CBCT) is an important tool facilitating computer aided interventions, despite often suffering from artifacts that pose challenges for accurate interp…
Inflation forecasting with attention based transformer neural networks
Maximilian Tschuchnig, Petra Tschuchnig, Cornelia Ferner +1
Inflation is a major determinant for allocation decisions and its forecast is a fundamental aim of governments and central banks. However, forecasting inflation is not a trivial ta…