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International Journal of Computer Assisted Radiology and Surgery

Erschienen in:

29.09.2022 | Original Article

DiffeoRaptor: diffeomorphic inter-modal image registration using RaPTOR

verfasst von: Nima Masoumi, Hassan Rivaz, M. Omair Ahmad, Yiming Xiao

Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 2/2023

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Abstract

Purpose

Diffeomorphic image registration is essential in many medical imaging applications. Several registration algorithms of such type have been proposed, but primarily for intra-contrast alignment. Currently, efficient inter-modal/contrast diffeomorphic registration, which is vital in numerous applications, remains a challenging task.

Methods

We proposed a novel inter-modal/contrast registration algorithm that leverages Robust PaTch-based cOrrelation Ratio metric to allow inter-modal/contrast image alignment and bandlimited geodesic shooting demonstrated in Fourier-Approximated Lie Algebras (FLASH) algorithm for fast diffeomorphic registration.

Results

The proposed algorithm, named DiffeoRaptor, was validated with three public databases for the tasks of brain and abdominal image registration while comparing the results against three state-of-the-art techniques, including FLASH, NiftyReg, and Symmetric image Normalization (SyN).

Conclusions

Our results demonstrated that DiffeoRaptor offered comparable or better registration performance in terms of registration accuracy. Moreover, DiffeoRaptor produces smoother deformations than SyN in inter-modal and contrast registration. The code for DiffeoRaptor is publicly available at https://github.com/nimamasoumi/DiffeoRaptor.

Vorheriger Artikel Multi-scale feature pyramid fusion network for medical image segmentation

Nächster Artikel Efficient contour-based annotation by iterative deep learning for organ segmentation from volumetric medical images

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Hernandez M, Bossa MN, Olmos S (2009) Registration of anatomical images using paths of diffeomorphisms parameterized with stationary vector field flows. Int J Comput Vis 85:291–306CrossRef

Tward D, Brown T, Kageyama Y, Patel J, Hou Z, Mori S, Albert M, Troncoso J, Miller M (2020) Diffeomorphic registration with intensity transformation and missing data: application to 3D digital pathology of Alzheimer’s disease. Front Neurosci 14:52CrossRef

Zhang M, Golland P (2016) Statistical shape analysis: from landmarks to diffeomorphisms. In: Medical image analysis, ISSN: 1361-8415, vol 33, pp 155–158

Blaiotta C, Freund P, Cardoso MJ, Ashburner J (2018) Generative diffeomorphic modelling of large MRI data sets for probabilistic template construction. NeuroImage 166:117–134CrossRef

Xu Z, Lee CP, Heinrich MP, Modat M, Rueckert D, Ourselin S, Abramson RG, Landman BA (2016) Evaluation of six registration methods for the human abdomen on clinically acquired CT. IEEE Trans Biomed Eng 63(8):1563–1572CrossRef

Beg M, Miller M, Trouvé A, Younes L (2005) Computing large deformation metric mappings via geodesic flows of diffeomorphisms. Int J Comput Vis 61(2):139–157CrossRef

Vialard FX, Risser L, Rueckert D, Cotter CJ (2012) Diffeomorphic 3D image registration via geodesic shooting using an efficient adjoint calculation. Int J Comput Vis 97(2):229–241CrossRef

Zhang M, Fletcher PT (2019) Fast diffeomorphic image registration via Fourier-approximated lie algebras. Int J Comput Vis 127:61–73CrossRef

Wu J, Tang X (2020) A large deformation diffeomorphic framework for fast brain image registration via parallel computing and optimization. Neuroinformatics 18:251–266CrossRef

10.

Chen X, Diaz-Pinto A, Ravikumar N, Frangi AF (2021) Deep learning in medical image registration. Prog Biomed Eng 3:012003

11.

Dalca AV, Balakrishnan G, Guttag J, Sabuncu MR (2019) Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces. Med Image Anal 57:226–236CrossRef

12.

Wang J, Zhang M (2020) Deepflash: an efficient network for learning-based medical image registration. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 4444–4452

13.

Hering A, Hansen L, Mok TC, Chung A, Siebert H, Her S, Lange A, Kuckertz S, Heldmann S, Shao W, Vesal S (2021) Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning. arXiv preprint arXiv:2112.04489

14.

Mitra J, Kato Z, Martí R, Oliver A, Lladó X, Sidibé D, Ghose S, Vilanova JC, Comet J, Meriaudeau F (2012) A spline-based non-linear diffeomorphism for multimodal prostate registration. Med Image Anal 16(6):1259–1279CrossRef

15.

Kutten KS, Charon N, Miller MI, Ratnanather JT, Mateisky J, Baden AD (2017) A large deformation diffeomorphic approach to registration of CLARITY images via mutual information. In: Medical image computing and computer assisted intervention—MICCAI, 2017, vol 10433. Lecture Notes in Computer Science. Springer, Cham

16.

Reaungamornrat S, Silva TD, Uneri A, Vogt S, Kleinszig G, Khanna AJ, Wolinsky JP, Prince JL, Siewerdsen JH (2016) MIND demons: symmetric diffeomorphic deformable registration of MR and CT for image-guided spine surgery. IEEE Trans Med Imaging 35(11):2413–2424CrossRef

17.

Avants BB, Epstein CL, Grossman M, Gee JC (2008) Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med Image Anal 12(1):26–41CrossRef

18.

Vercauteren T, Pennec X, Perchant A, Ayache N (2009) Diffeomorphic demons: efficient non-parametric image registration. Neuroimage 45(1 Suppl):S61-72CrossRef

19.

Heinrich MP, Jenkinson M, Bhushan M, Matin T, Gleeson FV, Brady M, Schnabel JA (2012) MIND: modality independent neighbourhood descriptor for multi-modal deformable registration. Med Image Anal 16(7):1423–1435CrossRef

20.

Rivaz H, Chen SJ, Collins DL (2015) Automatic deformable MR-ultrasound registration for image-guided neurosurgery. IEEE Trans Med Imaging 34(2):366–80CrossRef

21.

Mercier L, Maestro RFD, Petrecca K, Araujo D, Haegelen C, Collins DL (2012) Online database of clinical MR and ultrasound images of brain tumors. Med Phys 39:3253CrossRef

22.

Masoumi N, Xiao Y, Rivaz H (2019) ARENA: inter-modality affine registration using evolutionary strategy. Int J Comput Assist Radiol Surg 14:441–450CrossRef

23.

Xiao Y, Fortin M, Unsgård G, Rivaz H, Reinertsen I (2017) REtroSpective evaluation of cerebral tumors (RESECT): a clinical database of pre-operative MRI and intra-operative ultrasound in low-grade glioma surgeries. Med Phys 44:3875–3882CrossRef

24.

Masoumi N, Belasso CJ, Ahmad MO, Benali H, Xiao Y, Rivaz H (2021) Multimodal 3D ultrasound and CT in image-guided spinal surgery: public database and new registration algorithms. Int J Comput Assist Radiol Surg 16:555–565CrossRef

25.

Singh N, Hinkle J, Joshi S, Fletcher PT (2013) A vector momenta formulation of diffeomorphisms for improved geodesic regression and atlas construction. In: IEEE 10th international symposium on biomedical imaging, pp 1219–1222

26.

Oliveira FPM, Tavares JMRS (2014) Medical image registration: a review. Comput Methods Biomech Biomed Eng 17(2):73–93CrossRef

27.

Modat M, Ridgway GR, Taylor ZA, Lehmann M, Barnes J, Hawkes DJ, Fox NC, Ourselin S (2010) Fast free-form deformation using graphics processing units. Comput Methods Program Biomed 98(3):278–284CrossRef

28.

Miller MI, Trouvé A, Younes L (2006) Geodesic shooting for computational anatomy. J Math Imaging Vis 24:209–228CrossRef

29.

Joshi SC, Miller MI (2000) Landmark matching via large deformation diffeomorphisms. IEEE Trans Image Process 9(8):1357–1370CrossRef

30.

Roche A, Malandain G, Pennec X, Ayache N (1998) The correlation ratio as a new similarity measure for multimodal image registration. In: Medical image computing and computer-assisted intervention—MICCAI98, Lecture Notes in Computer Science, vol 1496. Springer, Berlin, Heidelberg

31.

LaMontagne PJ, Benzinger TL, Morris JC, Keefe S, Hornbeck R, Xiong C, Grant E, Hassenstab J, Moulder K, Vlassenko A Raichle ME (2019) OASIS-3: longitudinal neuroimaging, clinical, and cognitive dataset for normal aging and Alzheimer disease. MedRxiv

32.

Clark K, Vendt B, Smith K, Freymann J, Kirby J, Koppel P, Moore S, Phillips S, Maffitt D, Pringle M, Tarbox L, Prior F (2013) The cancer imaging archive (TCIA): maintaining and operating a public information repository. J Digit Imaging 26(6):1045–1057CrossRef

33.

Avants BB, Tustison N, Song G (2009) Advanced normalization tools (ANTS). Insight j 2(365):1–35

34.

Manjón JV, Coupé P (2016) volBrain: an online MRI brain volumetry system. Front Neuroinform 10:30CrossRef

35.

Manjón JV, Eskildsen S, Coupé P, Romero J, Collins L, Robles M (2014) NICE: nonlocal intracranial cavity extraction. Int J Biomed Imaging 4191:820205

36.

Grabner G, Janke AL, Budge MM, Smith D, Pruessner J, Collins DL (2006) Symmetric atlasing and model based segmentation: an application to the hippocampus in older adults. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv 9:58–66

37.

Rohlfing T (2011) Image similarity and tissue overlaps as surrogates for image registration accuracy: widely used but unreliable. IEEE Trans Med Imaging 31(2):153–163CrossRef

Titel: DiffeoRaptor: diffeomorphic inter-modal image registration using RaPTOR
verfasst von: Nima Masoumi
Hassan Rivaz
M. Omair Ahmad
Yiming Xiao
Publikationsdatum: 29.09.2022
Verlag: Springer International Publishing
Erschienen in: International Journal of Computer Assisted Radiology and Surgery / Ausgabe 2/2023
Print ISSN: 1861-6410
Elektronische ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-022-02749-2

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Abstract

Purpose

Methods

Results

Conclusions

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