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pro vyhledávání: '"lee, Kisuk"'
Autor:
Wei, Donglai, Lee, Kisuk, Li, Hanyu, Lu, Ran, Bae, J. Alexander, Liu, Zequan, Zhang, Lifu, Santos, Márcia dos, Lin, Zudi, Uram, Thomas, Wang, Xueying, Arganda-Carreras, Ignacio, Matejek, Brian, Kasthuri, Narayanan, Lichtman, Jeff, Pfister, Hanspeter
Electron microscopy (EM) enables the reconstruction of neural circuits at the level of individual synapses, which has been transformative for scientific discoveries. However, due to the complex morphology, an accurate reconstruction of cortical axons
Externí odkaz:
http://arxiv.org/abs/2107.05451
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: Ph. D. in Computation, Massachusetts Institute of Technology, Department of Brain and Cogni
Thesis: Ph. D. in Computation, Massachusetts Institute of Technology, Department of Brain and Cogni
Externí odkaz:
https://hdl.handle.net/1721.1/133076
Autor:
Seshamani, Sharmishtaa, Elabbady, Leila, Schneider-Mizell, Casey, Mahalingam, Gayathri, Dorkenwald, Sven, Bodor, Agnes, Macrina, Thomas, Bumbarger, Daniel, Buchanan, JoAnn, Takeno, Marc, Yin, Wenjing, Brittain, Derrick, Torres, Russel, Kapner, Daniel, lee, Kisuk, Lu, Ran, Wu, Jinpeng, daCosta, Nuno, Reid, Clay, Collman, Forrest
Morphology based analysis of cell types has been an area of great interest to the neuroscience community for several decades. Recently, high resolution electron microscopy (EM) datasets of the mouse brain have opened up opportunities for data analysi
Externí odkaz:
http://arxiv.org/abs/2006.00100
We show dense voxel embeddings learned via deep metric learning can be employed to produce a highly accurate segmentation of neurons from 3D electron microscopy images. A "metric graph" on a set of edges between voxels is constructed from the dense v
Externí odkaz:
http://arxiv.org/abs/1909.09872
Neural circuits can be reconstructed from brain images acquired by serial section electron microscopy. Image analysis has been performed by manual labor for half a century, and efforts at automation date back almost as far. Convolutional nets were fi
Externí odkaz:
http://arxiv.org/abs/1904.12966
It is now common to process volumetric biomedical images using 3D Convolutional Networks (ConvNets). This can be challenging for the teravoxel and even petavoxel images that are being acquired today by light or electron microscopy. Here we introduce
Externí odkaz:
http://arxiv.org/abs/1904.10489
Connectomics aims to recover a complete set of synaptic connections within a dataset imaged by volume electron microscopy. Many systems have been proposed for locating synapses, and recent research has included a way to identify the synaptic partners
Externí odkaz:
http://arxiv.org/abs/1904.09947
Autor:
Gornet, James, Venkataraju, Kannan Umadevi, Narasimhan, Arun, Turner, Nicholas, Lee, Kisuk, Seung, H. Sebastian, Osten, Pavel, Sümbül, Uygar
Reconstructing multiple molecularly defined neurons from individual brains and across multiple brain regions can reveal organizational principles of the nervous system. However, high resolution imaging of the whole brain is a technically challenging
Externí odkaz:
http://arxiv.org/abs/1903.07027
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