Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
368-01-014 ISMRM Abstract

Fully Automatic Slice-to-Volume MRI–Histology Registration: A Pilot Study on Myelin Staining

Primary: Analysis Methods - Image Registration and Alignment
Secondary: Neuro - Head & Neck/ENT
368-01-014 · Registration, Atlases, and Motion · Monday, 11 May, 8:20 AM–9:15 AM · Digital Posters Row I
Keywords: Image registration Histology Histology-MRI registration Multimodal image registration Slice-to-Volume registration
Accepted
Sutatip Pittayapong 1,2, Simon Hametner2,3, Beata Bachrata1, Verena Endmayr2,3, Christian Menard1, Wolfgang Bogner4,5, Romana Höftberger2,3, Guenther Grabner1
1Department of Medical Engineering, Carinthia University of Applied Sciences, Klagenfurt, Austria
2Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
3Comprehensive Center for Clinical Neurosciences and Mental Health, Medical University of Vienna, Vienna, Austria
4High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
5Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
Presenting Author: Sutatip Pittayapong

Synopsis

Motivation:
Goals:
Approach:
Results:
Full abstract & presentation

The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.

Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.

To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.

Log in

References

1. Gurcan, M. N., Boucheron, L. E., Can, A., Madabhushi, A., Rajpoot, N. M., & Yener, B. (2009). Histopathological image analysis: A review. IEEE Reviews in Biomedical Engineering, 2, 147–171. https://doi.org/10.1109/RBME.2009.2034865 [doi]
2. Lazari, A., & Lipp, I. (2021). Can MRI measure myelin? Systematic review, qualitative assessment, and meta-analysis of studies validating microstructural imaging with myelin histology. NeuroImage, 230, 117744. https://doi.org/10.1016/j.neuroimage.2021.117744 [doi]
3. Umemneku Chikere, C. M., Wilson, K., Graziadio, S., Vale, L., & Allen, A. J. (2019). Diagnostic test evaluation methodology: A systematic review of methods employed to evaluate diagnostic tests in the absence of gold standard - An update. PloS One, 14(10), e0223832. https://doi.org/10.1371/journal.pone.0223832 [doi]
4. Ohnishi, T., Nakamura, Y., Tanaka, T., Tanaka, T., Hashimoto, N., Haneishi, H., Batchelor, T. T., Gerstner, E. R., Taylor, J. W., Snuderl, M., & Yagi, Y. (2016). Deformable image registration between pathological images and MR image via an optical macro image. Pathology Research & Practice, 212(10), 927-936. https://doi.org/10.1016/j.prp.2016.07.018 [doi]
5. Goubran, M., de Ribaupierre, S., Hammond, R. R., Currie, C., Burneo, J. G., Parrent, A. G., Peters, T. M., & Khan, A. R. (2015). Registration of in-vivo to ex-vivo MRI of surgically resected specimens: A pipeline for histology to in-vivo registration. Journal of Neuroscience Methods, 241, 53–65. https://doi.org/10.1016/j.jneumeth.2014.12.005 [doi]
6. Alegro, M., Alho, E. J. L., Morais Martin, M. da G., Teneholz Grinberg, L., Heinsen, H., Lopes, R. de D., Amaro-Jr., E., Zöllei, L. (2016). Multimodal Whole Brain Registration: MRI and High Resolution Histology. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (pp. …). https://openaccess.thecvf.com/content_cvpr_2016_workshops/w15/papers/Alegro_Multimodal_Whole_Brain_CVPR_2016_paper.pdf
7. Mancini, M., Casamitjana, A., Peter, L., Robinson, E., Crampsie, S., Thomas, D. L., Holton, J. L., Jaunmuktane, Z., & Iglesias, J. E. (2020). A multimodal computational pipeline for 3D histology of the human brain. Scientific Reports, 10, Article 13839. https://doi.org/10.1038/s41598-020-69163-z [doi]
8. Iglesias, J. E., Modat, M., Peter, L., Stevens, A., Annunziata, R., Vercauteren, T., … Ourselin, S. (2018). Joint registration and synthesis using a probabilistic model for alignment of MRI and histological sections. Medical Image Analysis, 50, 127-144. https://doi.org/10.1016/j.media.2018.09.002 [doi]
9. Casamitjana, A., Lorenzi, M., Ferraris, S., Peter, L., Modat, M., Stevens, A., Fischl, B., Vercauteren, T., & Iglesias, J. E. (2022). Robust joint registration of multiple stains and MRI for multimodal 3D histology reconstruction: Application to the Allen human brain atlas. Medical Image Analysis, 75, 102265. https://doi.org/10.1016/j.media.2021.102265 [doi]
10. Shao, W., Banh, L., Kunder, C. A., Fan, R. E., Soerensen, S. J. C., Wang, J. B., …, Rusu, M. (2021). ProsRegNet: A deep learning framework for registration of MRI and histopathology images of the prostate. Medical Image Analysis, 68, 101919. https://doi.org/10.1016/j.media.2020.101919 [doi]
11. Alyami, W., Kyme, A., & Bourne, R. (2022). Histological validation of MRI: A review of challenges in registration of imaging and whole-mount histopathology. Journal of Magnetic Resonance Imaging, 55(1), 11-22. https://doi.org/10.1002/jmri.27409 [doi]
12. Pittayapong, S., Hametner, S., Bachratá, B., Endmayr, V., Bogner, W., Höftberger, R., & Grabner, G. (2025). Synthesized myelin and iron stainings from 7 T multi-contrast MRI via deep learning. NeuroImage, 318, 121417. https://doi.org/10.1016/j.neuroimage.2025.121417 [doi]
13. Tustison, N. J., Avants, B. B., Cook, P. A., Zheng, Y., Egan, A., Yushkevich, P. A., & Gee, J. C. (2010). N4itk: Improved N3 bias correction. IEEE Transactions on Medical Imaging, 29(6), 1310–1320. https://doi.org/10.1109/TMI.2010.2046908 [doi]
14. Billot, B., Greve, D. N., Puonti, O., Thielscher, A., van Leemput, K., Fischl, B., Dalca, A. V., & Iglesias, J. E. (2023). Synthseg: Segmentation of brain MRI scans of any contrast and resolution without retraining. Medical Image Analysis, 86, 102789. https://doi.org/10.1016/j.media.2023.102789 [doi]
15. Huang, G., Liu, Z., Van der Maaten, L., & Weinberger, K. Q. (2017). Densely connected convolutional networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 4700–4708). https://doi.org/10.1109/CVPR.2017.243 (Original work posted 2016 on arXiv:1608.06993 [doi]
16. Bookstein, F. L. (1989). Principal warps: Thin-plate splines and the decomposition of deformations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(6), 567–585. https://doi.org/10.1109/34.24792 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/368-01-014