Funcmasker-flex: An Automated BIDS-App for Brain Segmentation of Human Fetal Functional MRI data

Arroyo, M. S., Hopkin, R. J., Nagaraj, U. D., Kline-Fath, B., & Venkatesan, C. (2019). Fetal brain MRI findings and neonatal outcome of common diagnosis at a tertiary care center. Journal of Perinatology, 39(8), 1072–1077. https://doi.org/10.1038/s41372-019-0407-9

Article  PubMed  Google Scholar 

De Asis-Cruz (2022). FetalGAN: Automated Segmentation of Fetal Functional Brain MRI Using Deep Generative Adversarial Learning and Multi-Scale 3D U-Net. Front. Neurosci., 07 June 2022. Sec. Brain Imaging Methods. Volume 16– https://doi.org/10.3389/fnins.2022.887634

Esteban, O., Markiewicz, C. J., Blair, R. W., Moodie, C. A., Isik, A. I., Erramuzpe, A., Kent, J. D., Goncalves, M., DuPre, E., Snyder, M., Oya, H., Ghosh, S. S., Wright, J., Durnez, J., Poldrack, R. A., & Gorgolewski, K. J. (2019). fMRIPrep: A robust preprocessing pipeline for functional MRI. Nature Methods, 16(1), 111–116. https://doi.org/10.1038/s41592-018-0235-4

Article  CAS  PubMed  Google Scholar 

Huisman, T. A. G. M., Martin, E., Kubik-Huch, R., & Marincek, B. (2002). Fetal magnetic resonance imaging of the brain: Technical considerations and normal brain development. European Radiology, 12(8), 1941–1951. https://doi.org/10.1007/s00330-001-1209-x

Article  PubMed  Google Scholar 

Isensee, F., Jaeger, P. F., Kohl, S. A. A., Petersen, J., & Maier-Hein, K. H. (2021). nnU-Net: A self-configuring method for deep learning-based biomedical image segmentation. Nature Methods, 18(2), 203–211. https://doi.org/10.1038/s41592-020-01008-z

Article  CAS  PubMed  Google Scholar 

Kalavathi, P., & Prasath, V. B. S. (2016). Methods on Skull Stripping of MRI Head scan Images—a review. Journal of Digital Imaging, 29(3), 365–379. https://doi.org/10.1007/s10278-015-9847-8

Article  CAS  PubMed  Google Scholar 

Khan, A., & Haast, R. (2021). Snakebids - BIDS integration into snakemake workflows. https://doi.org/10.5281/ZENODO.4488249

McCarthy, P. (2021). FSLeyes. https://doi.org/10.5281/ZENODO.5576035

Prayer, D., Brugger, P. C., & Prayer, L. (2004). Fetal MRI: Techniques and protocols. Pediatric Radiology, 34(9), 685–693. https://doi.org/10.1007/s00247-004-1246-0

Article  PubMed  Google Scholar 

Rajagopalan, V., Deoni, S., Panigrahy, A., & Thomason, M. E. (2021). Is fetal MRI ready for neuroimaging prime time? An examination of progress and remaining areas for development. Developmental Cognitive Neuroscience, 51, 100999. https://doi.org/10.1016/j.dcn.2021.100999

Article  PubMed  PubMed Central  Google Scholar 

Ronneberger, O., Fischer, P., & Brox, T. (2015). U-Net: Convolutional Networks for Biomedical Image Segmentation. In N. Navab, J. Hornegger, W. Wells, & A. Frangi (Eds.), Medical Image Computing and Computer-Assisted intervention – MICCAI 2015 (9351 vol.). Cham: Springer. Lecture Notes in Computer Sciencehttps://doi.org/10.1007/978-3-319-24574-4_28

Chapter  Google Scholar 

Rousseau, F., Glenn, O. A., Iordanova, B., Rodriguez-Carranza, C., Vigneron, D. B., Barkovich, J. A., & Studholme, C. (2006). Registration-Based Approach for Reconstruction of High-Resolution in Utero fetal MR brain images. Academic Radiology, 13(9), 1072–1081. https://doi.org/10.1016/j.acra.2006.05.003

Article  PubMed  Google Scholar 

Rutherford, S., Sturmfels, P., Angstadt, M., Hect, J., Wiens, J., van den Heuvel, M. I., Scheinost, D., Sripada, C., & Thomason, M. (2021). Automated brain masking of fetal functional MRI with Open Data. Neuroinformatics. https://doi.org/10.1007/s12021-021-09528-5

Article  PubMed  PubMed Central  Google Scholar 

Shattuck, D. W., & Leahy, R. M. (2002). BrainSuite: An automated cortical surface identification tool. Medical Image Analysis, 6(2), 129–142. https://doi.org/10.1016/s1361-8415(02)00054-3

Article  PubMed  Google Scholar 

Smith, S. M. (2002). Fast robust automated brain extraction. Human Brain Mapping, 17(3), 143–155. https://doi.org/10.1002/hbm.10062

Article  PubMed  PubMed Central  Google Scholar 

Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., Niazy, R. K., Saunders, J., Vickers, J., Zhang, Y., De Stefano, N., Brady, J. M., & Matthews, P. M. (2004). Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage, 23(Suppl 1), 208–219. https://doi.org/10.1016/j.neuroimage.2004.07.051

Article  Google Scholar 

Thomason, M. E., Brown, J. A., Dassanayake, M. T., Shastri, R., Marusak, H. A., Hernandez-Andrade, E., Yeo, L., Mody, S., Berman, S., Hassan, S. S., & Romero, R. (2014). Intrinsic functional brain architecture derived from graph theoretical analysis in the human fetus. Plos One, 9(5), 1–10. https://doi.org/10.1371/journal.pone.0094423

Article  CAS  Google Scholar 

Thomason, M. E., Dassanayake, M. T., Shen, S., Katkuri, Y., Alexis, M., Anderson, A. L., Yeo, L., Mody, S., Hernandez-Andrade, E., Hassan, S. S., Studholme, C., Jeong, J. W., & Romero, R. (2013). Cross-hemispheric functional connectivity in the human fetal brain. Science Translational Medicine, 5(173), https://doi.org/10.1126/scitranslmed.3004978

Thomason, M. E., Grove, L. E., Lozon, T. A., Vila, A. M., Ye, Y., Nye, M. J., Manning, J. H., Pappas, A., Hernandez-Andrade, E., Yeo, L., Mody, S., Berman, S., Hassan, S. S., & Romero, R. (2015). Age-related increases in long-range connectivity in fetal functional neural connectivity networks in utero. Developmental Cognitive Neuroscience, 11, 96–104. https://doi.org/10.1016/j.dcn.2014.09.001

Article  PubMed  Google Scholar 

van den Heuvel, M. I., Turk, E., Manning, J. H., Hect, J., Hernandez-Andrade, E., Hassan, S. S., Romero, R., van den Heuvel, M. P., & Thomason, M. E. (2018). Hubs in the human fetal brain network. Developmental Cognitive Neuroscience, 30(February), 108–115. https://doi.org/10.1016/j.dcn.2018.02.001

Article  PubMed  PubMed Central  Google Scholar 

Wheelock, M. D., Hect, J. L., Hernandez-Andrade, E., Hassan, S. S., Romero, R., Eggebrecht, A. T., & Thomason, M. E. (2019). Sex differences in functional connectivity during fetal brain development. Developmental Cognitive Neuroscience, 36(May 2018), 100632. https://doi.org/10.1016/j.dcn.2019.100632

留言 (0)

沒有登入
gif