no code implementations • 16 Aug 2023 • Denis Kutnár, Ivan R Vogelius, Katrin Elisabet Håkansson, Jens Petersen, Jeppe Friborg, Lena Specht, Mogens Bernsdorf, Anita Gothelf, Claus Kristensen, Abraham George Smith
We investigated the extent to which a Convolutional neural network (CNN) is able to predict LRR volumes based on pre-treatment 18F-fluorodeoxyglucose positron emission tomography (FDG-PET)/computed tomography (CT) scans in HNSCC patients and thus the potential to identify biological high risk volumes using CNNs.
1 code implementation • 22 Jun 2021 • Abraham George Smith, Jens Petersen, Cynthia Terrones-Campos, Anne Kiil Berthelsen, Nora Jarrett Forbes, Sune Darkner, Lena Specht, Ivan Richter Vogelius
Organ-at-risk contouring is still a bottleneck in radiotherapy, with many deep learning methods falling short of promised results when evaluated on clinical data.