Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

A generative model for segmentation of tumor and organs-at-risk for radiation therapy planning of glioblastoma patients

Agn, Mikael ; Law, Ian ; Munck Af Rosenschöld, Per LU orcid and Van Leemput, Koen (2016) Medical Imaging 2016: Image Processing In Progress in Biomedical Optics and Imaging - Proceedings of SPIE 9784.
Abstract

We present a fully automated generative method for simultaneous brain tumor and organs-at-risk segmentation in multi-modal magnetic resonance images. The method combines an existing whole-brain segmentation technique with a spatial tumor prior, which uses convolutional restricted Boltzmann machines to model tumor shape. The method is not tuned to any specific imaging protocol and can simultaneously segment the gross tumor volume, peritumoral edema and healthy tissue structures relevant for radiotherapy planning. We validate the method on a manually delineated clinical data set of glioblastoma patients by comparing segmentations of gross tumor volume, brainstem and hippocampus. The preliminary results demonstrate the feasibility of the... (More)

We present a fully automated generative method for simultaneous brain tumor and organs-at-risk segmentation in multi-modal magnetic resonance images. The method combines an existing whole-brain segmentation technique with a spatial tumor prior, which uses convolutional restricted Boltzmann machines to model tumor shape. The method is not tuned to any specific imaging protocol and can simultaneously segment the gross tumor volume, peritumoral edema and healthy tissue structures relevant for radiotherapy planning. We validate the method on a manually delineated clinical data set of glioblastoma patients by comparing segmentations of gross tumor volume, brainstem and hippocampus. The preliminary results demonstrate the feasibility of the method.

(Less)
Please use this url to cite or link to this publication:
author
; ; and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Medical Imaging 2016 : Image Processing - Image Processing
series title
Progress in Biomedical Optics and Imaging - Proceedings of SPIE
editor
Styner, Martin A. and Angelini, Elsa D.
volume
9784
article number
97841D
publisher
SPIE
conference name
Medical Imaging 2016: Image Processing
conference location
San Diego, United States
conference dates
2016-03-01 - 2016-03-03
external identifiers
  • scopus:84981710043
ISSN
1605-7422
ISBN
9781510600195
DOI
10.1117/12.2216814
language
English
LU publication?
no
id
872a7f24-4ae5-4189-87fd-4ada085f1d53
date added to LUP
2020-07-28 09:04:09
date last changed
2023-07-20 08:31:44
@inproceedings{872a7f24-4ae5-4189-87fd-4ada085f1d53,
  abstract     = {{<p>We present a fully automated generative method for simultaneous brain tumor and organs-at-risk segmentation in multi-modal magnetic resonance images. The method combines an existing whole-brain segmentation technique with a spatial tumor prior, which uses convolutional restricted Boltzmann machines to model tumor shape. The method is not tuned to any specific imaging protocol and can simultaneously segment the gross tumor volume, peritumoral edema and healthy tissue structures relevant for radiotherapy planning. We validate the method on a manually delineated clinical data set of glioblastoma patients by comparing segmentations of gross tumor volume, brainstem and hippocampus. The preliminary results demonstrate the feasibility of the method.</p>}},
  author       = {{Agn, Mikael and Law, Ian and Munck Af Rosenschöld, Per and Van Leemput, Koen}},
  booktitle    = {{Medical Imaging 2016 : Image Processing}},
  editor       = {{Styner, Martin A. and Angelini, Elsa D.}},
  isbn         = {{9781510600195}},
  issn         = {{1605-7422}},
  language     = {{eng}},
  month        = {{01}},
  publisher    = {{SPIE}},
  series       = {{Progress in Biomedical Optics and Imaging - Proceedings of SPIE}},
  title        = {{A generative model for segmentation of tumor and organs-at-risk for radiation therapy planning of glioblastoma patients}},
  url          = {{http://dx.doi.org/10.1117/12.2216814}},
  doi          = {{10.1117/12.2216814}},
  volume       = {{9784}},
  year         = {{2016}},
}