A multimodal computational pipeline for 3D histology of the human brain.
作者： Matteo Mancini , Adrià Casamitjana , Loic Peter , Eleanor Robinson , Shauna Crampsie
DOI: 10.1038/S41598-020-69163-Z
关键词:
摘要: Ex vivo imaging enables analysis of the human brain at a level detail that is not possible in with MRI. In particular, histology can be used to study tissue microscopic level, using wide array different stains highlight microanatomical features. Complementing MRI has important applications ex atlas building and modeling link between microstructure macroscopic MR signal. However, requires sectioning tissue, hence distorting its 3D structure, particularly larger samples. Here, we present an open-source computational pipeline produce consistent reconstructions brain. The relies on volumetric scan serves as undistorted reference, intermediate modality (blockface photography) bridges gap histology. We results reconstruction whole hemispheres from two donors.
nature.com
sci-hub.st 参考文章(99)
Arnauld Sergé, Anne-Laure Bailly, Michel Aurrand-Lions, Beat A. Imhof, Magali Irla, For3D: Full organ reconstruction in 3D, an automatized tool for deciphering the complexity of lymphoid organs. Journal of Immunological Methods. ,vol. 424, pp. 32- 42 ,(2015) , 10.1016/J.JIM.2015.04.019
Vincent Arsigny, Olivier Commowick, Xavier Pennec, Nicholas Ayache, A Log-Euclidean Framework for Statistics on Diffeomorphisms Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006. ,vol. 9, pp. 924- 931 ,(2006) , 10.1007/11866565_113
Juan Eugenio Iglesias, Ender Konukoglu, Darko Zikic, Ben Glocker, Koen Van Leemput, Bruce Fischl, Is Synthesizing MRI Contrast Useful for Inter-modality Analysis? medical image computing and computer assisted intervention. ,vol. 16, pp. 631- 638 ,(2013) , 10.1007/978-3-642-40811-3_79
Herbert Bay, Tinne Tuytelaars, Luc Van Gool, SURF: speeded up robust features european conference on computer vision. ,vol. 1, pp. 404- 417 ,(2006) , 10.1007/11744023_32
Karen Simonyan, Andrew Zisserman, Very Deep Convolutional Networks for Large-Scale Image Recognition computer vision and pattern recognition. ,(2014)
Jonathan Long, Evan Shelhamer, Trevor Darrell, Fully convolutional networks for semantic segmentation computer vision and pattern recognition. pp. 3431- 3440 ,(2015) , 10.1109/CVPR.2015.7298965
Rushin Shojaii, Stephanie Bacopulos, Wenyi Yang, Tigran Karavardanyan, Demetri Spyropoulos, Afshin Raouf, Anne Martel, Arun Seth, Reconstruction of 3-dimensional histology volume and its application to study mouse mammary glands. Journal of Visualized Experiments. ,(2014) , 10.3791/51325
Daniel H. Adler, John Pluta, Salmon Kadivar, Caryne Craige, James C. Gee, Brian B. Avants, Paul A. Yushkevich, Histology-derived volumetric annotation of the human hippocampal subfields in postmortem MRI NeuroImage. ,vol. 84, pp. 505- 523 ,(2014) , 10.1016/J.NEUROIMAGE.2013.08.067
J. Annese, D.M. Sforza, M. Dubach, D. Bowden, A.W. Toga, Postmortem high-resolution 3-dimensional imaging of the primate brain: blockface imaging of perfusion stained tissue NeuroImage. ,vol. 30, pp. 61- 69 ,(2006) , 10.1016/J.NEUROIMAGE.2005.03.043
Herbert Thiele, Stefan Heldmann, Dennis Trede, Jan Strehlow, Stefan Wirtz, Wolfgang Dreher, Judith Berger, Janina Oetjen, Jan Hendrik Kobarg, Bernd Fischer, Peter Maass, 2D and 3D MALDI-imaging: conceptual strategies for visualization and data mining. Biochimica et Biophysica Acta. ,vol. 1844, pp. 117- 137 ,(2014) , 10.1016/J.BBAPAP.2013.01.040