A unified framework for focal intensity change detection and deformable image registration. Application to the monitoring of multiple sclerosis lesions in longitudinal 3D brain MRI
Registration is a crucial step in the design of automatic change detection methods dedicated to longitudinal brain MRI. Even small registration inaccuracies can significantly deteriorate the detection performance by introducing numerous spurious detections. Rigid or affine registration are usually c...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-12-01
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| Series: | Frontiers in Neuroimaging |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fnimg.2022.1008128/full |
| _version_ | 1797979211746508800 |
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| author | Eléonore Dufresne Denis Fortun Stéphane Kremer Stéphane Kremer Vincent Noblet |
| author_facet | Eléonore Dufresne Denis Fortun Stéphane Kremer Stéphane Kremer Vincent Noblet |
| author_sort | Eléonore Dufresne |
| collection | DOAJ |
| description | Registration is a crucial step in the design of automatic change detection methods dedicated to longitudinal brain MRI. Even small registration inaccuracies can significantly deteriorate the detection performance by introducing numerous spurious detections. Rigid or affine registration are usually considered to align baseline and follow-up scans, as a pre-processing step before applying a change detection method. In the context of multiple sclerosis, using deformable registration can be required to capture the complex deformations due to brain atrophy. However, non-rigid registration can alter the shape of appearing and evolving lesions while minimizing the dissimilarity between the two images. To overcome this issue, we consider registration and change detection as intertwined problems that should be solved jointly. To this end, we formulate these two separate tasks as a single optimization problem involving a unique energy that models their coupling. We focus on intensity-based change detection and registration, but the approach is versatile and could be extended to other modeling choices. We show experimentally on synthetic and real data that the proposed joint approach overcomes the limitations of the sequential scheme. |
| first_indexed | 2024-04-11T05:35:20Z |
| format | Article |
| id | doaj.art-f87544ab66c248d9a0283d25f30a1b65 |
| institution | Directory Open Access Journal |
| issn | 2813-1193 |
| language | English |
| last_indexed | 2024-04-11T05:35:20Z |
| publishDate | 2022-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroimaging |
| spelling | doaj.art-f87544ab66c248d9a0283d25f30a1b652022-12-22T14:29:52ZengFrontiers Media S.A.Frontiers in Neuroimaging2813-11932022-12-01110.3389/fnimg.2022.10081281008128A unified framework for focal intensity change detection and deformable image registration. Application to the monitoring of multiple sclerosis lesions in longitudinal 3D brain MRIEléonore Dufresne0Denis Fortun1Stéphane Kremer2Stéphane Kremer3Vincent Noblet4ICube UMR 7357, Université de Strasbourg, CNRS, Strasbourg, FranceICube UMR 7357, Université de Strasbourg, CNRS, Strasbourg, FranceICube UMR 7357, Université de Strasbourg, CNRS, Strasbourg, FranceHôpitaux Universitaires de Strasbourg, Strasbourg, FranceICube UMR 7357, Université de Strasbourg, CNRS, Strasbourg, FranceRegistration is a crucial step in the design of automatic change detection methods dedicated to longitudinal brain MRI. Even small registration inaccuracies can significantly deteriorate the detection performance by introducing numerous spurious detections. Rigid or affine registration are usually considered to align baseline and follow-up scans, as a pre-processing step before applying a change detection method. In the context of multiple sclerosis, using deformable registration can be required to capture the complex deformations due to brain atrophy. However, non-rigid registration can alter the shape of appearing and evolving lesions while minimizing the dissimilarity between the two images. To overcome this issue, we consider registration and change detection as intertwined problems that should be solved jointly. To this end, we formulate these two separate tasks as a single optimization problem involving a unique energy that models their coupling. We focus on intensity-based change detection and registration, but the approach is versatile and could be extended to other modeling choices. We show experimentally on synthetic and real data that the proposed joint approach overcomes the limitations of the sequential scheme.https://www.frontiersin.org/articles/10.3389/fnimg.2022.1008128/fulldeformable 3D registrationchange detectionlongitudinal analysismultiple sclerosisjoint minimizationalternating direction method of multipliers (ADMM) |
| spellingShingle | Eléonore Dufresne Denis Fortun Stéphane Kremer Stéphane Kremer Vincent Noblet A unified framework for focal intensity change detection and deformable image registration. Application to the monitoring of multiple sclerosis lesions in longitudinal 3D brain MRI Frontiers in Neuroimaging deformable 3D registration change detection longitudinal analysis multiple sclerosis joint minimization alternating direction method of multipliers (ADMM) |
| title | A unified framework for focal intensity change detection and deformable image registration. Application to the monitoring of multiple sclerosis lesions in longitudinal 3D brain MRI |
| title_full | A unified framework for focal intensity change detection and deformable image registration. Application to the monitoring of multiple sclerosis lesions in longitudinal 3D brain MRI |
| title_fullStr | A unified framework for focal intensity change detection and deformable image registration. Application to the monitoring of multiple sclerosis lesions in longitudinal 3D brain MRI |
| title_full_unstemmed | A unified framework for focal intensity change detection and deformable image registration. Application to the monitoring of multiple sclerosis lesions in longitudinal 3D brain MRI |
| title_short | A unified framework for focal intensity change detection and deformable image registration. Application to the monitoring of multiple sclerosis lesions in longitudinal 3D brain MRI |
| title_sort | unified framework for focal intensity change detection and deformable image registration application to the monitoring of multiple sclerosis lesions in longitudinal 3d brain mri |
| topic | deformable 3D registration change detection longitudinal analysis multiple sclerosis joint minimization alternating direction method of multipliers (ADMM) |
| url | https://www.frontiersin.org/articles/10.3389/fnimg.2022.1008128/full |
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