@article {65253,
	title = {Tissue clearing and its applications in neuroscience},
	journal = {Nature Reviews Neuroscience},
	year = {2020},
	month = {2020 Feb 1},
	abstract = {<p>State-of-the-art tissue-clearing methods provide subcellular-level optical access to intact tissues from individual organs and even to some entire mammals. When combined with light-sheet microscopy and automated approaches to image analysis, existing tissue-clearing methods can speed up and may reduce the cost of conventional histology by several orders of magnitude. In addition, tissue-clearing chemistry allows whole-organ antibody labelling, which can be applied even to thick human tissues. By combining the most powerful labelling, clearing, imaging and data-analysis tools, scientists are extracting structural and functional cellular and subcellular information on complex mammalian bodies and large human specimens at an accelerated pace. The rapid generation of terabyte-scale imaging data furthermore creates a high demand for efficient computational approaches that tackle challenges in large-scale data analysis and management. In this Review, we discuss how tissue-clearing methods could provide an unbiased, system-level view of mammalian bodies and human specimens and discuss future opportunities for the use of these methods in human neuroscience.</p>
},
	issn = {1471-003X},
	doi = {10.1038/s41583-019-0250-1},
	url = {http://www.nature.com/articles/s41583-019-0250-1},
	author = {Ueda, Hiroki R. and Ert{\"u}rk, Ali and Chung, Kwanghun and Gradinaru, Viviana and Ch{\'e}dotal, Alain and Tomancak, Pavel and Keller, Philipp J.}
}
@article {65079,
	title = {BigStitcher: reconstructing high-resolution image datasets of cleared and expanded samples.},
	journal = {Nature Methods},
	volume = {16},
	year = {2019},
	month = {2019 Sep},
	pages = {870-74},
	abstract = {<p>Light-sheet imaging of cleared and expanded samples creates terabyte-sized datasets that consist of many unaligned three-dimensional image tiles, which must be reconstructed before analysis. We developed the BigStitcher software to address this challenge. BigStitcher enables interactive visualization, fast and precise alignment, spatially resolved quality estimation, real-time fusion and deconvolution of dual-illumination, multitile, multiview datasets. The software also compensates for optical effects, thereby improving accuracy and enabling subsequent biological analysis.</p>
},
	issn = {1548-7091},
	doi = {10.1038/s41592-019-0501-0},
	url = {http://www.nature.com/articles/s41592-019-0501-0http://www.nature.com/articles/s41592-019-0501-0.pdfhttp://www.nature.com/articles/s41592-019-0501-0.pdfhttp://www.nature.com/articles/s41592-019-0501-0},
	author = {H{\"o}rl, David and Rojas Rusak, Fabio and Preusser, Friedrich and Tillberg, Paul and Randel, Nadine and Chhetri, Raghav K. and Cardona, Albert and Keller, Philipp J. and Harz, Hartmann and Leonhardt, Heinrich and Treier, Mathias and Preibisch, Stephan}
}
