eprintid: 1501088
rev_number: 37
eprint_status: archive
userid: 608
dir: disk0/01/50/10/88
datestamp: 2017-03-08 12:48:53
lastmod: 2021-10-10 22:59:53
status_changed: 2017-03-08 12:48:53
type: proceedings_section
metadata_visibility: show
creators_name: Burgos, N
creators_name: Guerreiro, F
creators_name: McClelland, J
creators_name: Nill, S
creators_name: Dearnaley, D
creators_name: Desouza, N
creators_name: Oelfke, U
creators_name: Knopf, AC
creators_name: Ourselin, S
creators_name: Cardoso, MJ
title: Joint segmentation and CT synthesis for MRI-only radiotherapy treatment planning
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F42
note: Copyright © Springer International Publishing AG 2016.
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-46723-8_63
abstract: Accurate knowledge of organ location and tissue attenuation properties are the two essential components to perform radiotherapy treatment planning (RTP). Computed tomography (CT) has been the modality of choice for RTP as it easily provides electron density information. However, its low soft tissue contrast limits the accuracy of organ delineation. On the contrary, magnetic resonance (MR) provides images with excellent soft tissue contrast but its use for RTP is limited by the fact that it does not readily provide tissue attenuation information.

In this work we propose a multi-atlas information propagation scheme that jointly segments the organs at risk and generates pseudo CT data from MR images. We demonstrate that the proposed framework is able to automatically generate accurate pseudo CT images and segmentations in the pelvic region, bypassing the need for CT scan for accurate RTP.
date: 2016-10-02
date_type: published
publisher: Springer
official_url: https://doi.org/10.1007/978-3-319-46723-8_63
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1137826
doi: 10.1007/978-3-319-46723-8_63
isbn_13: 9783319467221
lyricists_name: Burgos, Ninon
lyricists_name: Cardoso, Manuel
lyricists_name: McClelland, James
lyricists_name: Ourselin, Sebastien
lyricists_id: BURGO78
lyricists_id: MJMCA47
lyricists_id: JRMCC68
lyricists_id: SOURS59
actors_name: Burgos, Ninon
actors_id: BURGO78
actors_role: owner
full_text_status: public
series: Lecture Notes in Computer Science
publication: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
volume: 9901
place_of_pub: Cham, Switzerland
pagerange: 547-555
event_title: MICCAI 2016: Medical Image Computing and Computer-Assisted Intervention
issn: 1611-3349
book_title: International Conference on Medical Image Computing and Computer-Assisted Intervention
editors_name: Ourselin, S
editors_name: Joskowicz, L
editors_name: Sabuncu, M
editors_name: Unal, G
editors_name: Wells, W
citation:        Burgos, N;    Guerreiro, F;    McClelland, J;    Nill, S;    Dearnaley, D;    Desouza, N;    Oelfke, U;             ... Cardoso, MJ; + view all <#>        Burgos, N;  Guerreiro, F;  McClelland, J;  Nill, S;  Dearnaley, D;  Desouza, N;  Oelfke, U;  Knopf, AC;  Ourselin, S;  Cardoso, MJ;   - view fewer <#>    (2016)    Joint segmentation and CT synthesis for MRI-only radiotherapy treatment planning.                     In: Ourselin, S and Joskowicz, L and Sabuncu, M and Unal, G and Wells, W, (eds.) International Conference on Medical Image Computing and Computer-Assisted Intervention.  (pp. pp. 547-555).  Springer: Cham, Switzerland.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/1501088/1/miccai_2016_ninon_final_version.pdf