Liliana Petrychenko- Netherlands Cancer Institute
Liliana Petrychenko
- Netherlands Cancer Institute
About
5
Publications
116
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Introduction
Skills and Expertise
Current institution
Publications
Publications (5)
This study aims to assess and compare two state-of-the-art deep learning approaches for segmenting four thoracic organs at risk (OAR)—the esophagus, trachea, heart, and aorta—in CT images in the context of radiotherapy planning.
We compare a multi-organ segmentation approach and the fusion of multiple single-organ models, each dedicated to one OAR....
We explore deep generative models to generate case-based explanations in a medical federated learning setting. Explaining AI model decisions through case-based interpretability is paramount to increasing trust and allowing widespread adoption of AI in clinical practice. However, medical AI training paradigms are shifting towards federated learning...
Background
The Response Evaluation Criteria in Solid Tumors (RECIST) aims to provide a standardized approach to assess treatment response in solid tumors. However, discrepancies in the selection of measurable and target lesions among radiologists using these criteria pose a significant limitation to their reproducibility and accuracy. This study ai...
