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Dataset / Electron Microscopic Data Analysis

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Title
Electron Microscopic Data Analysis
Date Created and/or Issued
2019-01 to 2019-06
Contributing Institution
UC San Diego, Research Data Curation Program
Collection
Data Science & Engineering Master of Advanced Study (DSE MAS) Capstone Projects
Rights Information
Under copyright
Constraint(s) on Use: This work is protected by the U.S. Copyright Law (Title 17, U.S.C.). Use of this work beyond that allowed by "fair use" or any license applied to this work requires written permission of the copyright holder(s). Responsibility for obtaining permissions and any use and distribution of this work rests exclusively with the user and not the UC San Diego Library. Inquiries can be made to the UC San Diego Library program having custody of the work.
Use: This work is available from the UC San Diego Library. This digital copy of the work is intended to support research, teaching, and private study.
Rights Holder and Contact
Singhal, Tushar; Kolkur, Prashant
Description
Capstone Project for Data Science & Engineering Master's Program at UC Sand Diego (UCSD) 2019. The “Electron Microscopic Data Analysis” project aims to support the processing, analysis and dissemination of large-scale 3D electron microscopic (EM) data derived from a remarkable collection of legacy biopsy brain samples from patients suffering from Alzheimer’s disease (AD). Alzheimer’s disease is a progressive neurodegenerative disease, leading to dementia accompanied by several structural changes in the brain of patients. The project intends to facilitate the processing and downstream analysis of complete whole cell reconstructions of neurons from unique biopsy image samples of cerebral cortex taken from AD cases by Robert Terry in the 1960’s, focusing on early onset cases, where cells effected to differing extents are neighbored by cells without AD-associated forming paired helical filaments, (PHF) now known to be largely made up of tau proteins. These samples were screened and preliminarily reported on by Ellisman, Masliah and Terry (Ellisman et al., 1987) and manifest near perfect preservation of ultrastructure PHF and amyloid accumulations as well as modifications to subcellular organelles and cytoskeletons of the cell bodies, axonal and dendritic processes. Raw data (or data) is coming from Cell Image Library (CIL: http://cellimagelibrary.org/cdeep3m). Cell Image library is a public and easily accessible resource database of images, videos, and animations of cells, capturing a wide diversity of organisms, cell types, and cellular processes. The purpose of this database is to advance research on cellular activity, with the ultimate goal of improving human health. This data is accessed manually from the website and copied to the memory disk for processing. The data is a serial block face scanning electron microscopy (SBEM) 3D data volumes. Serial block-face scanning electron microscopy (SBEM) is a way to obtain high resolution 3D images from a sample. This method is particularly good at imaging large fields-of-view in X,Y,Z that is 3dimension at nanometer resolution. The data is brain image samples of patients suffering from Alzheimer’s disease. The Alzheimer's image data images are of very high definition. The size of a typical image in multiple datasets is in the range of 16000x10000x400 pixels images.
Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp)
Singhal, Tushar; Kolkur, Prashant; Ellisman, Mark H.; Altintas, Ilkay (2019). Electron Microscopic Data Analysis. In Data Science & Engineering Master of Advanced Study (DSE MAS) Capstone Projects. UC San Diego Library Digital Collections. https://doi.org/10.6075/J03N21QH
Type
dataset
Identifier
ark:/20775/bb3281205b
Subject
Data Science & Engineering Master of Advanced Study (DSE MAS)
Nuclei
Mitochondria
DeepEM3D
Vesicles
MultiResUnet
Convolutional Neural Network (CNN)
P100 latency
Menbranes
Neural networks (Computer science)
Cell Image Library (CIL)
Alzheimer's disease Serial block-face scanning electron microscopy (SBEM)
Big data
Capstone projects
CDeep3M
DSE MAS - 2019 Cohort

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