@inproceedings{b2c46912e78f435dae0bf64e397eeaa5,
title = "Towards automatic plan selection for radiotherapy of cervical cancer by fast automatic segmentation of cone beam CT scans",
abstract = "We propose a method to automatically select a treatment plan for radiotherapy of cervical cancer using a Plan-of-the-Day procedure, in which multiple treatment plans are constructed prior to treatment. The method comprises a multi-atlas based segmentation algorithm that uses the selected treatment plan to choose between two atlas sets. This segmentation only requires two registration procedures and can therefore be used in clinical practice without using excessive computation time. Our method is validated on a dataset of 224 treatment fractions for 10 patients. In 37 cases (16\%), no recommendation was made by the algorithm due to poor image quality or registration results. In 93\% of the remaining cases a correct recommendation for a treatment plan was given.",
author = "Thomas Langerak and Sabrina Heijkoop and Sandra Quint and Mens, \{Jan Willem\} and Ben Heijmen and Mischa Hoogeman",
note = "{\textcopyright} 2014 Springer International Publishing Switzerland ; 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 ; Conference date: 14-09-2014 Through 18-09-2014",
year = "2014",
doi = "10.1007/978-3-319-10404-1\_66",
language = "English",
isbn = "978-3-319-10403-4",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science+Business Media",
number = "PART 1",
pages = "528--535",
booktitle = "Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014",
}
