Localization and Registration of 2D Histological Mouse Brain Images in 3D Atlas Space

Abdelmoula, W. M., Carreira, R. J., Shyti, R., Balluff, B., van Zeijl, R. J., Tolner, E. A., Lelieveldt, B. F., van den Maagdenberg, A. M., McDonnell, L. A., & Dijkstra, J. (2014). Automatic registration of mass spectrometry imaging data sets to the Allen brain Atlas. Analytical Chemistry, 86(8), 3947–3954.

Article  CAS  PubMed  Google Scholar 

Agarwal, N., Xu, X., & Gopi, M. (2017). Automatic detection of histological artifacts in mouse brain slice images. In Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging: MICCAI 2016 International Workshops, MCV and BAMBI, Athens, Greece, October 21, 2016, Revised Selected Papers 8 (pp. 105–115). Springer.

Allen Institute. Allen Mouse Brain Atlas. Retrieved March 2020, from: http://mouse.brain-map.org/

Allen Institute. Informatics Archive of the Allen Institute. Retrieved January 2021, from: http://download.alleninstitute.org/informatics-archive/current-release/mouse_ccf/annotation/

Bai, J., Trinh, T. L. H., Chuang, K.-H., & Qiu, A. (2012). Atlas-based automatic mouse brain image segmentation revisited: Model complexity vs. image registration. Magnetic Resonance Imaging, 30(6), 789–798.

Article  PubMed  Google Scholar 

Beg, M. F., Miller, M. I., Trouvé, A., & Younes, L. (2005). Computing large deformation metric mappings via geodesic flows of diffeomorphisms. International Journal of Computer Vision, 61, 139–157.

Article  Google Scholar 

Carey, H., Pegios, M., Martin, L., Saleeba, C., Turner, A., Everett, N., Puchades, M., Bjaalie, J., & McMullan, S. (2022). Deepslice: Rapid fully automatic registration of mouse brain imaging to a volumetric atlas. bioRxiv, 2022–04.

Dice, L. R. (1945). Measures of the amount of ecologic association between species. Ecology, 26(3), 297–302.

Article  Google Scholar 

He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 770–778).

Iqbal, A., Sheikh, A., & Karayannis, T. (2019). Denerd: High-throughput detection of neurons for brain-wide analysis with deep learning. Scientific Reports, 9(1), 13828.

Article  PubMed  PubMed Central  Google Scholar 

ITK. Insight Segmentation and Registration Toolkit. Retrieved April 2020, from: https://itk.org

Jin, M., Nguyen, J. D., Weber, S. J., Mejias-Aponte, C. A., Madangopal, R., & Golden, S. A. (2022). Smart: An open-source extension of wholebrain for intact mouse brain registration and segmentation. Eneuro, 9(3).

Kim, Y., Venkataraju, K. U., Pradhan, K., Mende, C., Taranda, J., Turaga, S. C., Arganda-Carreras, I., Ng, L., Hawrylycz, M. J., Rockland, K. S., et al. (2015). Mapping social behavior-induced brain activation at cellular resolution in the mouse. Cell reports, 10(2), 292–305.

Article  CAS  PubMed  Google Scholar 

Krepl, J., Casalegno, F., Delattre, E., Erö, C., Lu, H., Keller, D., Rodarie, D., Markram, H., & Schürmann, F. (2021). Supervised learning with perceptual similarity for multimodal gene expression registration of a mouse brain atlas. Frontiers in Neuroinformatics, 15, 691918.

Article  PubMed  PubMed Central  Google Scholar 

Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007). Genome-wide atlas of gene expression in the adult mouse brain. Nature, 445(7124), 168–176.

Article  CAS  PubMed  Google Scholar 

Leung, K. K., Barnes, J., Ridgway, G. R., Bartlett, J. W., Clarkson, M. J., Macdonald, K., Schuff, N., Fox, N. C., Ourselin, S., Initiative, A. D. N., et al. (2010). Automated cross-sectional and longitudinal hippocampal volume measurement in mild cognitive impairment and Alzheimer’s disease. Neuroimage, 51(4), 1345–1359.

Article  PubMed  Google Scholar 

Lin, R., Wang, R., Yuan, J., Feng, Q., Zhou, Y., Zeng, S., Ren, M., Jiang, S., Ni, H., Zhou, C., et al. (2018). Cell-type-specific and projection-specific brain-wide reconstruction of single neurons. Nature Methods, 15(12), 1033–1036.

Article  CAS  PubMed  Google Scholar 

Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., & Suetens, P. (1997). Multimodality image registration by maximization of mutual information. IEEE transactions on Medical Imaging, 16(2), 187–198.

Article  CAS  PubMed  Google Scholar 

Maintz, J. A., & Viergever, M. A. (1998). A survey of medical image registration. Medical Image Analysis, 2(1), 1–36.

Article  CAS  PubMed  Google Scholar 

Majka, P., & Wójcik, D. K. (2016). Possum-a framework for three-dimensional reconstruction of brain images from serial sections. Neuroinformatics, 14, 265–278.

Article  PubMed  Google Scholar 

Miyamichi, K., Amat, F., Moussavi, F., Wang, C., Wickersham, I., Wall, N. R., Taniguchi, H., Tasic, B., Huang, Z. J., He, Z., et al. (2011). Cortical representations of olfactory input by trans-synaptic tracing. Nature, 472(7342), 191–196.

Article  CAS  PubMed  Google Scholar 

Neurodata. (2023). Ardent python package. Retrieved June 2020, from: https://ardent.neurodata.io

Niedworok, C. J., Brown, A. P., Jorge Cardoso, M., Osten, P., Ourselin, S., Modat, M., & Margrie, T. W. (2016). amap is a validated pipeline for registration and segmentation of high-resolution mouse brain data. Nature Communications, 7(1), 11879.

Article  PubMed  PubMed Central  Google Scholar 

Ni, H., Tan, C., Feng, Z., Chen, S., Zhang, Z., Li, W., Guan, Y., Gong, H., Luo, Q., & Li, A. (2020). A robust image registration interface for large volume brain atlas. Scientific Reports, 10(1), 1–16.

Article  Google Scholar 

Oh, S. W., Harris, J. A., Ng, L., Winslow, B., Cain, N., Mihalas, S., Wang, Q., Lau, C., Kuan, L., Henry, A. M., et al. (2014). A mesoscale connectome of the mouse brain. Nature, 508(7495), 207–214.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Pallast, N., Wieters, F., Fink, G. R., & Aswendt, M. (2019). Atlas-based imaging data analysis tool for quantitative mouse brain histology (Aidahisto). Journal of Neuroscience Methods, 326, 108394.

Article  CAS  PubMed  Google Scholar 

Papp, E. A., Leergaard, T. B., Calabrese, E., Johnson, G. A., & Bjaalie, J. G. (2014). Waxholm space atlas of the sprague dawley rat brain. Neuroimage, 97, 374–386.

Article  PubMed  Google Scholar 

Paşca, S. P. (2018). The rise of three-dimensional human brain cultures. Nature, 553(7689), 437–445.

Article  PubMed  Google Scholar 

Piluso, S., Souedet, N., Jan, C., Clouchoux, C., & Delzescaux, T. (2021). Automated atlas-based segmentation of single coronal mouse brain slices using linear 2D-2d registration. In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 2860–2863). IEEE.

Puchades, M. A., Csucs, G., Ledergerber, D., Leergaard, T. B., & Bjaalie, J. G. (2019). Spatial registration of serial microscopic brain images to three-dimensional reference atlases with the Quicknii tool. PloS one, 14(5), 0216796.

Article  Google Scholar 

Qu, L., Li, Y., Xie, P., Liu, L., Wang, Y., Wu, J., Liu, Y., Wang, T., Li, L., Guo, K., et al. (2022). Cross-modal coherent registration of whole mouse brains. Nature Methods, 19(1), 111–118.

Article  CAS  PubMed  Google Scholar 

Ragan, T., Kadiri, L. R., Venkataraju, K. U., Bahlmann, K., Sutin, J., Taranda, J., Arganda-Carreras, I., Kim, Y., Seung, H. S., & Osten, P. (2012). Serial two-photon tomography for automated ex vivo mouse brain imaging. Nature Methods, 9(3), 255–258.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ramos-Prats, A., Paradiso, E., Castaldi, F., Sadeghi, M., Mir, M. Y., Hörtnagl, H., Göbel, G., & Ferraguti, F. (2022). VIP-expressing interneurons in the anterior insular cortex contribute to sensory processing to regulate adaptive behavior. Cell Reports, 39(9), 110893.

Article  CAS  PubMed  Google Scholar 

Renier, N., Adams, E. L., Kirst, C., Wu, Z., Azevedo, R., Kohl, J., Autry, A. E., Kadiri, L., Venkataraju, K. U., Zhou, Y., et al. (2016). Mapping of brain activity by automated volume analysis of immediate early genes. Cell, 165(7), 1789–1802.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ronneberger, O., Fischer, P., & Brox, T. (2015). U-net: Convolutional networks for biomedical image segmentation. In Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 18 (pp. 234–241). Springer.

Roy, D. S., Park, Y.-G., Kim, M. E., Zhang, Y., Ogawa, S. K., DiNapoli, N., Gu, X., Cho, J. H., Choi, H., Kamentsky, L., et al. (2022). Brain-wide mapping reveals that engrams for a single memory are distributed across multiple brain regions. Nature Communications, 13(1), 1799.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., & Chen, L.-C. (2018). Mobilenetv2: Inverted residuals and linear bottlenecks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4510–4520).

Song, J. H., Choi, W., Song, Y.-H., Kim, J.-H., Jeong, D., Lee, S.-H., & Paik, S.-B. (2020). Precise mapping of single neurons by calibrated 3D reconstruction of brain slices reveals topographic projection in mouse visual cortex. Cell Reports, 31(8), 107682.

Article  CAS  PubMed  Google Scholar 

Tappan, S. J., Eastwood, B. S., O’Connor, N., Wang, Q., Ng, L., Feng, D., Hooks, B. M., Gerfen, C. R., Hof, P. R., Schmitz, C., et al. (2019). Automatic navigation system for the mouse brain. Journal of Comparative Neurology, 527(13), 2200–2211.

Article  PubMed  Google Scholar 

Tward, D., Li, X., Huo, B., Lee, B., Mitra, P., & Miller, M. (2019). 3D mapping of serial histology sections with anomalies using a novel robust deformable registration algorithm. In Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy: 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings (pp. 162–173). Springer.

Wang, Q., Ding, S.-L., Li, Y., Royall, J., Feng, D., Lesnar, P., Graddis, N., Naeemi, M., Facer, B., Ho, A., et al. (2020). The Allen mouse brain common coordinate framework: A 3D reference atlas. Cell, 181(4), 936–953.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Wang, Y., Li, Q., Liu, L., Zhou, Z., Ruan, Z., Kong, L., Li, Y., Wang, Y., Zhong, N., Chai, R., et al. (2019). Teravr empowers precise reconstruction of complete 3-D neuronal morphology in the whole brain. Nature Communications, 10(1), 3474.

Article  PubMed  PubMed Central  Google Scholar 

Wang, S., Niu, K., Chen, L., & Rao, X. (2022). Method for counting labeled neurons in mouse brain regions based on image representation and registration. Medical & Biological Engineering & Computing, 60(2), 487–500.

Article  Google Scholar 

Wang, X., Zeng, W., Yang, X., Zhang, Y., Fang, C., Zeng, S., Han, Y., & Fei, P. (2021). Bi-channel image registration and deep-learning segmentation (birds) for efficient, versatile 3D mapping of mouse brain. Elife, 10, 63455.

Article  Google Scholar 

Xiong, J., Ren, J., Luo, L., & Horowitz, M. (2018). Mapping histological slice sequences to the Allen mouse brain atlas without 3D reconstruction. Frontiers in Neuroinformatics, 12, 93.

Article  PubMed  PubMed Central  Google Scholar 

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