Oncology

F₁ Workflow Improvement of Image-guided Radiotherapy: Fast On-line Adaptive MR-guided Radiotherapy Treatment of High-risk Prostate Cancer Patients

Oncology Radiotherapy

We are investigating an alternative radiotherapy treatment workflow on the MR-Linac for high-risk prostate cancer patients.

Emma ten Hoor, Bas Raaymakers, Josien Pluim, Hans de Boer

Case F (1): Workflow Improvement of Image-guided Radiotherapy: Fast On-line Adaptive MR-guided Radiotherapy Treatment of High-risk Prostate Cancer Patients

F₂ Workflow Improvement of Image-guided Radiotherapy: Segmentation Uncertainty Quantification for Improving the Image-Guided Radiotherapy Workflow

Oncology Radiotherapy

We investigate how the image-guided radiotherapy workflow can be improved, in terms of efficiency and safety, by processing uncertainty estimations obtained during deep learning auto-contouring.

Ruben Stoffijn, Josien Pluim, Nico van den Berg, Hans de Boer

Case F (2): Workflow Improvement of Image-guided Radiotherapy: Segmentation Uncertainty Quantification for Improving the Image-Guided Radiotherapy Workflow

K Automated generation of radiology reports from thorax-abdomen CT scans

This PhD aims to develop an AI system that generates structured reports from CT scans to help radiologists work more efficiently amid a growing workforce shortage and rising cancer rates.

Theodoor Akkerboom, Clarisa Sánchez

Case K: Automated generation of radiology reports from thorax-abdomen CT scans