Conference item
Optimised misalignment correction from cine MR slices using statistical shape model
- Abstract:
- Cardiac magnetic resonance (CMR) imaging is a valuable imaging technique for the diagnosis and characterisation of cardiovascular diseases. In clinical practice, it is commonly acquired as a collection of separated and independent 2D image planes, limiting its accuracy in 3D analysis. One of the major issues for 3D reconstruction of human heart surfaces from CMR slices is the misalignment between heart slices, often arising from breathing or subject motion. In this regard, the objective of this work is to develop a method for optimal correction of slice misalignments using a statistical shape model (SSM), for accurate 3D modelling of the heart. After extracting the heart contours from 2D cine slices, we perform initial misalignment corrections using the image intensities and the heart contours. Next, our proposed misalignment correction is performed by first optimally fitting an SSM to the sparse heart contours in 3D space and then optimally aligning the heart slices on the SSM, accounting for both in-plane and out-of-plane misalignments. The performance of the proposed approach is evaluated on a cohort of 20 subjects selected from the UK Biobank study, demonstrating an average reduction of misalignment artifacts from 1.14±0.23 mm to 0.72±0.11 mm, in terms of distance from the final reconstructed 3D mesh.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 5.3MB, Terms of use)
-
- Publisher copy:
- 10.1007/978-3-030-80432-9_16
Authors
+ British Heart Foundation
More from this funder
- Funder identifier:
- http://dx.doi.org/10.13039/501100000274
- Grant:
- HSR01230
- Publisher:
- Springer
- Host title:
- Medical Image Understanding and Analysis
- Pages:
- 201–209
- Series:
- Lecture Notes in Computer Science
- Series number:
- 12722
- Place of publication:
- Cham, Switzerland
- Publication date:
- 2021-07-06
- Event title:
- 25th UK Conference on Medical Image Understanding and Analysis (MIUA 2021)
- Event location:
- Oxford, UK
- Event website:
- https://miua2021.com/
- Event start date:
- 2021-07-12
- Event end date:
- 2021-07-14
- DOI:
- EISSN:
-
1611-3349
- ISSN:
-
0302-9743
- EISBN:
- 9783030804329
- ISBN:
- 9783030804312
- Language:
-
English
- Keywords:
- Pubs id:
-
1185458
- Local pid:
-
pubs:1185458
- Deposit date:
-
2022-12-31
Terms of use
- Copyright holder:
- Springer Nature Switzerland AG
- Copyright date:
- 2021
- Rights statement:
- © 2021 Springer Nature Switzerland AG.
- Notes:
- This is the accepted manuscript version of the paper. The final version is available online from Springer at: https://doi.org/10.1007/978-3-030-80432-9_16
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