@inproceedings{fac925d882eb455485cd834d545e4fcb,
title = "Prediction of brain MR scans in longitudinal tumor follow-up studies",
abstract = "We present a new method for the estimation of the next brain MR scan in a longitudinal tumor follow-up study. Our method effectively incorporates information of the past scans in the time series to predict the future scan of the patient. Its advantages are that it requires no user intervention and does not assume any particular tumor growth model. Instead, the patient-specific tumor growth parameters are estimated individually from the past patient scans. To validate our method, we conducted an experimental study on four patients with Optic Path Gliomas (OPGs) and four patients with glioblastomas multiforma (GBM), each scanned at five time points. The tumor volumes in the predicted and actual future scans, both segmented by an expert radiologist, yield a mean volume overlap difference of 13.65% for the OPG patients, and 34.23% for the GBM patients.",
author = "Lior Weizman and Liat Ben-Sira and Leo Joskowicz and Orna Aizenstein and Ben Shofty and Shlomi Constantini and Dafna Ben-Bashat",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2012.; 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012 ; Conference date: 05-10-2012 Through 05-10-2012",
year = "2012",
doi = "10.1007/978-3-642-33418-4_23",
language = "אנגלית",
isbn = "9783642334177",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "179--187",
editor = "Georg Langs and Albert Montillo and Menze, {Bjoern H.} and Antonio Criminisi and Zhuowen Tu and Le Lu and Georg Langs and Nicholas Ayache and Herv{\'e} Delingette and Menze, {Bjoern H.} and Polina Golland and Kensaku Mori",
booktitle = "Medical Image Computing and Computer-Assisted Intervention - MICCAI2012 - 15th International Conference, Proceedings",
}