Abstractocyte: A Visual Tool for Exploring Nanoscale Astroglial Cells

Handle URI:
http://hdl.handle.net/10754/624967
Title:
Abstractocyte: A Visual Tool for Exploring Nanoscale Astroglial Cells
Authors:
Mohammed, Haneen ( 0000-0002-4535-1926 )
Abstract:
This thesis presents the design and implementation of Abstractocyte, a system for the visual analysis of astrocytes, and their relation to neurons, in nanoscale volumes of brain tissue. Astrocytes are glial cells, i.e., non-neuronal cells that support neurons and the nervous system. Even though glial cells make up around 50 percent of all cells in the mammalian brain, so far they have been far less studied than neurons. Nevertheless, the study of astrocytes has immense potential for understanding brain function. However, the complex and widely-branching structure of astrocytes requires high-resolution electron microscopy imaging and makes visualization and analysis challenging. Using Abstractocyte, biologists can explore the morphology of astrocytes at various visual abstraction levels, while simultaneously analyzing neighboring neurons and their connectivity. We define a novel, conceptual 2D abstraction space for jointly visualizing astrocytes and neurons. Neuroscientists can choose a joint visualization as a specific point in that 2D abstraction space. Dragging this point allows them to smoothly transition between different abstraction levels in an intuitive manner. We describe the design of Abstractocyte, and present three case studies in which neuroscientists have successfully used our system to assess astrocytic coverage of synapses, glycogen distribution in relation to synapses, and astrocytic-mitochondria coverage.
Advisors:
Hadwiger, Markus ( 0000-0003-1239-4871 )
Committee Member:
Gao, Xin ( 0000-0002-7108-3574 ) ; Ravasi, Timothy ( 0000-0002-9950-465X ) ; Cali, Corrado
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Program:
Computer Science
Issue Date:
12-Jun-2017
Type:
Thesis
Appears in Collections:
Theses

Full metadata record

DC FieldValue Language
dc.contributor.advisorHadwiger, Markusen
dc.contributor.authorMohammed, Haneenen
dc.date.accessioned2017-06-13T05:44:42Z-
dc.date.available2017-06-13T05:44:42Z-
dc.date.issued2017-06-12-
dc.identifier.urihttp://hdl.handle.net/10754/624967-
dc.description.abstractThis thesis presents the design and implementation of Abstractocyte, a system for the visual analysis of astrocytes, and their relation to neurons, in nanoscale volumes of brain tissue. Astrocytes are glial cells, i.e., non-neuronal cells that support neurons and the nervous system. Even though glial cells make up around 50 percent of all cells in the mammalian brain, so far they have been far less studied than neurons. Nevertheless, the study of astrocytes has immense potential for understanding brain function. However, the complex and widely-branching structure of astrocytes requires high-resolution electron microscopy imaging and makes visualization and analysis challenging. Using Abstractocyte, biologists can explore the morphology of astrocytes at various visual abstraction levels, while simultaneously analyzing neighboring neurons and their connectivity. We define a novel, conceptual 2D abstraction space for jointly visualizing astrocytes and neurons. Neuroscientists can choose a joint visualization as a specific point in that 2D abstraction space. Dragging this point allows them to smoothly transition between different abstraction levels in an intuitive manner. We describe the design of Abstractocyte, and present three case studies in which neuroscientists have successfully used our system to assess astrocytic coverage of synapses, glycogen distribution in relation to synapses, and astrocytic-mitochondria coverage.en
dc.language.isoenen
dc.subjectbiomedicalen
dc.subjectvisualizationen
dc.subjectvisual designen
dc.subjectabstraction techniquesen
dc.titleAbstractocyte: A Visual Tool for Exploring Nanoscale Astroglial Cellsen
dc.typeThesisen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
thesis.degree.grantorKing Abdullah University of Science and Technologyen_GB
dc.contributor.committeememberGao, Xinen
dc.contributor.committeememberRavasi, Timothyen
dc.contributor.committeememberCali, Corradoen
thesis.degree.disciplineComputer Scienceen
thesis.degree.nameMaster of Scienceen
dc.person.id128619en
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