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Proceedings Paper

Whole-body diffusion-weighted MR image stitching and alignment to anatomical MRI
Author(s): Jakub Ceranka; Mathias Polfliet; Frederic Lecouvet; Nicolas Michoux; Jef Vandemeulebroucke
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Paper Abstract

Whole-body diffusion-weighted (WB-DW) MRI in combination with anatomical MRI has shown a great poten- tial in bone and soft tissue tumour detection, evaluation of lymph nodes and treatment response assessment. Because of the vast body coverage, whole-body MRI is acquired in separate stations, which are subsequently combined into a whole-body image. However, inter-station and inter-modality image misalignments can occur due to image distortions and patient motion during acquisition, which may lead to inaccurate representations of patient anatomy and hinder visual assessment. Automated and accurate whole-body image formation and alignment of the multi-modal MRI images is therefore crucial. We investigated several registration approaches for the formation or stitching of the whole-body image stations, followed by a deformable alignment of the multi- modal whole-body images. We compared a pairwise approach, where diffusion-weighted (DW) image stations were sequentially aligned to a reference station (pelvis), to a groupwise approach, where all stations were simultaneously mapped to a common reference space while minimizing the overall transformation. For each, a choice of input images and corresponding metrics was investigated. Performance was evaluated by assessing the quality of the obtained whole-body images, and by verifying the accuracy of the alignment with whole-body anatomical sequences. The groupwise registration approach provided the best compromise between the formation of WB- DW images and multi-modal alignment. The fully automated method was found to be robust, making its use in the clinic feasible.

Paper Details

Date Published: 24 February 2017
PDF: 9 pages
Proc. SPIE 10133, Medical Imaging 2017: Image Processing, 1013311 (24 February 2017); doi: 10.1117/12.2253838
Show Author Affiliations
Jakub Ceranka, Vrije Univ. Brussel (Belgium)
IMEC (Belgium)
Mathias Polfliet, Vrije Univ. Brussel (Belgium)
IMEC (Belgium)
Erasmus MC (Belgium)
Frederic Lecouvet, Univ. Catholique de Louvain (Belgium)
Nicolas Michoux, Univ. Catholique de Louvain (Belgium)
Jef Vandemeulebroucke, Vrije Univ. Brussel (Belgium)
IMEC (Belgium)


Published in SPIE Proceedings Vol. 10133:
Medical Imaging 2017: Image Processing
Martin A. Styner; Elsa D. Angelini, Editor(s)

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