Robust CT synthesis for radiotherapy planning: Application to the head and neck region

TY - CHAP

T1 - Robust CT synthesis for radiotherapy planning

T2 - 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015

AU - Burgos, Ninon

AU - Cardoso, M. Jorge

AU - Guerreiro, Filipa

AU - Veiga, Catarina

AU - Modat, Marc

AU - McClelland, Jamie

AU - Knopf, Antje Christin

AU - Punwani, Shonit

AU - Atkinson, David

AU - Arridge, Simon R.

AU - Hutton, Brian F.

AU - Ourselin, Sébastien

PY - 2015/1/1

Y1 - 2015/1/1

N2 - In this work, we propose to tackle the problem of magnetic resonance (MR)-based radiotherapy treatment planning in the head & neck area by synthesising computed tomography (CT) from MR images using an iterative multi-atlas approach. The proposed method relies on pre-acquired pairs of non-rigidly aligned T2-weighted MRI and CT images of the neck. To synthesise a pseudo CT, all the MRIs in the database are first registered to the target MRI using a robust affine followed by a deformable registration. An initial pseudo CT is obtained by fusing the mapped atlases according to their morphological similarity to the target. This initial pseudo CT is then combined with the target MR image in order to improve both the registration and fusion stages and refine the synthesis in the bone region. Results showed that the proposed iterative CT synthesis algorithm is able to generate pseudo CT images in a challenging region for registration algorithms. We demonstrate that the robust affine decreases the overall absolute error compared to a single affine transformation, mainly in images with small axial field-of-view, whilst the bone refinement process further reduces the error in the bone region, increasing image sharpness.

AB - In this work, we propose to tackle the problem of magnetic resonance (MR)-based radiotherapy treatment planning in the head & neck area by synthesising computed tomography (CT) from MR images using an iterative multi-atlas approach. The proposed method relies on pre-acquired pairs of non-rigidly aligned T2-weighted MRI and CT images of the neck. To synthesise a pseudo CT, all the MRIs in the database are first registered to the target MRI using a robust affine followed by a deformable registration. An initial pseudo CT is obtained by fusing the mapped atlases according to their morphological similarity to the target. This initial pseudo CT is then combined with the target MR image in order to improve both the registration and fusion stages and refine the synthesis in the bone region. Results showed that the proposed iterative CT synthesis algorithm is able to generate pseudo CT images in a challenging region for registration algorithms. We demonstrate that the robust affine decreases the overall absolute error compared to a single affine transformation, mainly in images with small axial field-of-view, whilst the bone refinement process further reduces the error in the bone region, increasing image sharpness.

UR - http://www.scopus.com/inward/record.url?scp=84951047428&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-24571-3_57

DO - 10.1007/978-3-319-24571-3_57

M3 - Conference paper

AN - SCOPUS:84951047428

SN - 9783319245706

SN - 9783319245706

SN - 9783319245706

VL - 9350

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 476

EP - 484

BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings

PB - Springer Verlag

Y2 - 5 October 2015 through 9 October 2015

ER -