Ádám Kékesi

Automated MR-only radiotherapy outperforms CT-based radiotherapy and decreases hands-on time for head-and-neck cancer treatment

Iris Lauwers, Marta Ewa Capala, Sandeep Kaushik, László Ruskó et autres

Introduction: Cancer incidence is expected to increase in Europe by 18% in eighteen years. To account for the increasing patient numbers, the workload per patient needs to be reduced. One step towards future-proof radiotherapy is automated MR-only radiotherapy as it could eliminate …

nl, ch, de, hu, gb (code pays fourni par la source)

3319 Automated MR-only radiotherapy outperforms conventional MR-CT based radiotherapy in accuracy for head-and-neck cancer (MEC-2019-0805)

Iris Lauwers, Marta Ewa Capala, Sandeep S. Kaushik, László Ruskó et autres

2511 Evaluation of SAM and SAM2 from clinical perspective for organ delineation

Borbála Deák-Karancsi, Zsófia Karancsi, Ádám Kékesi, Eszter Katalin Kiss et autres

Comprehensive deep learning-based framework for automatic organs-at-risk segmentation in head-and-neck and pelvis for MR-guided radiation therapy planning

Vanda Czipczer, Bernadett Kolozsvári, Borbála Deák-Karancsi, Marta Ewa Capala et autres

Introduction: The excellent soft-tissue contrast of magnetic resonance imaging (MRI) is appealing for delineation of organs-at-risk (OARs) as it is required for radiation therapy planning (RTP). In the last decade there has been an increasing interest in using deep-learning (DL) techniques to …

hu, nl, gb, de, us (code pays fourni par la source)