Index

Investigating the Influence of Using Different for Detecting Parkinson’s Disease

Integrating Transformer Networks with Multi-Modal Learning for Document Layout Analysis

A Cascaded Encoder–Decoder Network for CT Image Restoration

Evaluate LORA finetuning for detection guided segmentation in CT images

Evaluation of LoRa tuning of grounded segmentation using MedSam. We will investigate if we can reduce the training parameters for optimal detection and segmentation performnce using SOTA methods and training paradigms on an Abdominal RSNA dataset.

Improving localization of VL models in CXRs

Patient-Specific Quality Assurance of Synthetic CT for MR-Only Radiotherapy

If you are interested in the thesis project, please send your application (CV, letter of motivation, current transcript
of records) with subject ’sCT PSQA – Thesis’ to: bernd-niklas.axer@extern.uk-erlangen.de

Data-Driven Characterization and Modeling of the Radiotherapy Workflow

If you are interested in the project, please send your curriculum vitæ to: rafael.lobao@uk-erlangen.de
Having prior experience with Python, SQL, and statistics is advantageous.

Field of Study: Medical Engineering / Data Science

Large Kernel Convolution for CT Image Restoration

Transfer learning Based Forecasting Of Heat Pump Energy Consumption Across Multiple Time Horizons

Reduction of die trials via machine learning approaches