Accurate localization in autonomous robots enables effective decision-making within their operating environment. Various methods have been developed to address this challenge, encompassing traditional techniques, fiducial marker utilization, and machine learning approaches. This work proposes a deep-learning …

The use of machine learning in embedded systems is an interesting topic, especially with the growth in popularity of the Internet of Things (IoT). The capacity of a system, such as a robot, to self-localize, is a fundamental skill for its navigation and decision-making processes. This work focuses on …

Localization is a crucial skill in mobile robotics because the robot needs to make reasonable navigation decisions to complete its mission. Many approaches exist to implement localization, but artificial intelligence can be an interesting alternative to traditional localization techniques based on model …

Abstract Background: The benefit of MR-only workflow compared to current CT-based workflow for prostate radiotherapy is reduction of systematic errors in the radiotherapy chain by 2–3 mm. Nowadays, MRI is used for target delineation while CT is needed for position verification. In MR-only workflows, …

Wereldwijd worden jaarlijks 800.000 mannen met prostaatkanker gediagnosticeerd. Radiotherapie is een veel gebruikte behandeling voor prostaatkanker. Processen rondom radiotherapie brengen onzekerheden met zich mee die ondervangen worden door passende marges rond het doelvolume te hanteren. Onzekerheden …

Abstract gepubliseerd in Elsevier: For patients with intermediate- and high risk prostate cancer, treated with high dose radiotherapy, the CTV generally involves the prostate and (part of) the seminal vesicles (SV) [1,2]. Fiducial markers locate the prostate reliably during radiotherapy [3]. However …