61 citations · 61 across the 2 of their papers we have counts for
2 papers
eess.IV2025
Improving the U-Net Configuration for Automated Delineation of Head and Neck Cancer on MRI
Andrei Iantsen
Tumor volume segmentation on MRI is a challenging and time-consuming process that is performed manually in typical clinical settings. This work presents an approach to automated de…
eess.IV2021★ 61 cited
Squeeze-and-Excitation Normalization for Automated Delineation of Head and Neck Primary Tumors in Combined PET and CT Images
Andrei Iantsen, Dimitris Visvikis, Mathieu Hatt
Development of robust and accurate fully automated methods for medical image segmentation is crucial in clinical practice and radiomics studies. In this work, we contributed an aut…