Zobrazeno 1 - 10
of 666
pro vyhledávání: '"Michael I Miller"'
Autor:
Michael Hawrylycz, Maryann E Martone, Giorgio A Ascoli, Jan G Bjaalie, Hong-Wei Dong, Satrajit S Ghosh, Jesse Gillis, Ronna Hertzano, David R Haynor, Patrick R Hof, Yongsoo Kim, Ed Lein, Yufeng Liu, Jeremy A Miller, Partha P Mitra, Eran Mukamel, Lydia Ng, David Osumi-Sutherland, Hanchuan Peng, Patrick L Ray, Raymond Sanchez, Aviv Regev, Alex Ropelewski, Richard H Scheuermann, Shawn Zheng Kai Tan, Carol L Thompson, Timothy Tickle, Hagen Tilgner, Merina Varghese, Brock Wester, Owen White, Hongkui Zeng, Brian Aevermann, David Allemang, Seth Ament, Thomas L Athey, Cody Baker, Katherine S Baker, Pamela M Baker, Anita Bandrowski, Samik Banerjee, Prajal Bishwakarma, Ambrose Carr, Min Chen, Roni Choudhury, Jonah Cool, Heather Creasy, Florence D'Orazi, Kylee Degatano, Benjamin Dichter, Song-Lin Ding, Tim Dolbeare, Joseph R Ecker, Rongxin Fang, Jean-Christophe Fillion-Robin, Timothy P Fliss, James Gee, Tom Gillespie, Nathan Gouwens, Guo-Qiang Zhang, Yaroslav O Halchenko, Nomi L Harris, Brian R Herb, Houri Hintiryan, Gregory Hood, Sam Horvath, Bingxing Huo, Dorota Jarecka, Shengdian Jiang, Farzaneh Khajouei, Elizabeth A Kiernan, Huseyin Kir, Lauren Kruse, Changkyu Lee, Boudewijn Lelieveldt, Yang Li, Hanqing Liu, Lijuan Liu, Anup Markuhar, James Mathews, Kaylee L Mathews, Chris Mezias, Michael I Miller, Tyler Mollenkopf, Shoaib Mufti, Christopher J Mungall, Joshua Orvis, Maja A Puchades, Lei Qu, Joseph P Receveur, Bing Ren, Nathan Sjoquist, Brian Staats, Daniel Tward, Cindy T J van Velthoven, Quanxin Wang, Fangming Xie, Hua Xu, Zizhen Yao, Zhixi Yun, Yun Renee Zhang, W Jim Zheng, Brian Zingg
Publikováno v:
PLoS Biology, Vol 21, Iss 6, p e3002133 (2023)
Characterizing cellular diversity at different levels of biological organization and across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also essential to manipulate cell typ
Externí odkaz:
https://doaj.org/article/5683e726eb424a3187544a44691a1d0f
Autor:
Austin R Graves, Richard H Roth, Han L Tan, Qianwen Zhu, Alexei M Bygrave, Elena Lopez-Ortega, Ingie Hong, Alina C Spiegel, Richard C Johnson, Joshua T Vogelstein, Daniel J Tward, Michael I Miller, Richard L Huganir
Publikováno v:
eLife, Vol 10 (2021)
Elucidating how synaptic molecules such as AMPA receptors mediate neuronal communication and tracking their dynamic expression during behavior is crucial to understand cognition and disease, but current technological barriers preclude large-scale exp
Externí odkaz:
https://doaj.org/article/bbc936d28bba4fee99a9525f2f0b9c39
Autor:
Meng Kuan Lin, Yeonsook Shin Takahashi, Bing-Xing Huo, Mitsutoshi Hanada, Jaimi Nagashima, Junichi Hata, Alexander S Tolpygo, Keerthi Ram, Brian C Lee, Michael I Miller, Marcello GP Rosa, Erika Sasaki, Atsushi Iriki, Hideyuki Okano, Partha Mitra
Publikováno v:
eLife, Vol 8 (2019)
Understanding the connectivity architecture of entire vertebrate brains is a fundamental but difficult task. Here we present an integrated neuro-histological pipeline as well as a grid-based tracer injection strategy for systematic mesoscale connecti
Externí odkaz:
https://doaj.org/article/0b60076348c449909442c99721a14dcb
Autor:
Alexandra Badea, Kwan L Ng, Robert J Anderson, Jiangyang Zhang, Michael I Miller, Richard J O'Brien
Publikováno v:
PLoS ONE, Vol 14, Iss 5, p e0216596 (2019)
We do not have a full understanding of the mechanisms underlying plasticity in the human brain. Mouse models have well controlled environments and genetics, and provide tools to help dissect the mechanisms underlying the observed responses to therapi
Externí odkaz:
https://doaj.org/article/980752181f064b5ead26b9876118ab26
Publikováno v:
PLoS Computational Biology, Vol 14, Iss 12, p e1006610 (2018)
This paper presents a variational framework for dense diffeomorphic atlas-mapping onto high-throughput histology stacks at the 20 μm meso-scale. The observed sections are modelled as Gaussian random fields conditioned on a sequence of unknown sectio
Externí odkaz:
https://doaj.org/article/897dff815dea4e9fab7d693ae2f7020f
Publikováno v:
PLoS ONE, Vol 13, Iss 7, p e0200294 (2018)
Multi-atlas brain segmentation of human brain MR images allows quantification research in structural neuroimaging. To achieve high accuracy and computational efficiency of segmentation relies on a custom subset of atlases for each target subject. How
Externí odkaz:
https://doaj.org/article/848eab68a8bd4fa09d124c3f1199e645
Autor:
Michael I Miller, J Tilak eRatnanather, Daniel J. Tward, Timothy eBrown, David S Lee, Michael eKetcha, Kanami eMori, Mei-Chang eWang, Susumu eMori, Marilyn S Albert, Laurent eYounes
Publikováno v:
Frontiers in Bioengineering and Biotechnology, Vol 3 (2015)
This paper examines MRI analysis of neurodegeneration in Alzheimer’s Disease (AD) in a network of structures within the medial temporal lobe using diffeomorphometry methods coupled with high-field atlasing in which the entorhinal cortex is partitio
Externí odkaz:
https://doaj.org/article/02dc80ad75744e32a0d523b398aa1859
Autor:
Xiaoying eTang, Deana eCrocetti, Kwame eKutten, Can eCeritoglu, Marilyn S Albert, Susumu eMori, Stewart H Mostofsky, Michael I Miller
Publikováno v:
Frontiers in Neuroscience, Vol 9 (2015)
We propose a hierarchical pipeline for skull-stripping and segmentation of anatomical structures of interest from T1-weighted images of the human brain. The pipeline is constructed based on a two-level Bayesian parameter estimation algorithm called m
Externí odkaz:
https://doaj.org/article/4ca0f1d245c3403db2b676f6e7a7ee52
Autor:
Zifei Liang, Xiaohai He, Can Ceritoglu, Xiaoying Tang, Yue Li, Kwame S Kutten, Kenichi Oishi, Michael I Miller, Susumu Mori, Andreia V Faria
Publikováno v:
PLoS ONE, Vol 10, Iss 7, p e0133533 (2015)
Brain parcellation tools based on multiple-atlas algorithms have recently emerged as a promising method with which to accurately define brain structures. When dealing with data from various sources, it is crucial that these tools are robust for many
Externí odkaz:
https://doaj.org/article/822e251a8f9144a4928e3cd5242db221
Publikováno v:
PLoS ONE, Vol 9, Iss 1, p e85580 (2014)
To evaluate the accuracy of advanced non-linear registration of serial lung Computed Tomography (CT) images using Large Deformation Diffeomorphic Metric Mapping (LDDMM).FIFTEEN CASES OF LUNG CANCER WITH SERIAL LUNG CT IMAGES (INTERVAL: 62.2±26.9 day
Externí odkaz:
https://doaj.org/article/74bcde14019b43c69c99fbb7da70c60d