Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/179729
COMPARTIR / EXPORTAR:
logo share SHARE BASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE

Invitar a revisión por pares abierta
Título

Synaptic cleft segmentation in non-isotropic volume electron microscopy of the complete drosophila brain

AutorHeinrich, Larissa; Funke, Jan CSIC ORCID; Pape, Constantin; Nunez-Iglesias, Juan; Saalfeld, Stephan
Fecha de publicaciónsep-2018
EditorSpringer Nature
CitaciónMedical Image Computing and Computer Assisted Intervention – MICCAI 2018: 317-325 (2018)
SerieLecture Notes in Computer Science
11071
ResumenNeural circuit reconstruction at single synapse resolution is increasingly recognized as crucially important to decipher the function of biological nervous systems. Volume electron microscopy in serial transmission or scanning mode has been demonstrated to provide the necessary resolution to segment or trace all neurites and to annotate all synaptic connections. Automatic annotation of synaptic connections has been done successfully in near isotropic electron microscopy of vertebrate model organisms. Results on non-isotropic data in insect models, however, are not yet on par with human annotation. We designed a new 3D-U-Net architecture to optimally represent isotropic fields of view in non-isotropic data. We used regression on a signed distance transform of manually annotated synaptic clefts of the CREMI challenge dataset to train this model and observed significant improvement over the state of the art. We developed open source software for optimized parallel prediction on very large volumetric datasets and applied our model to predict synaptic clefts in a 50 tera-voxels dataset of the complete Drosophila brain. Our model generalizes well to areas far away from where training data was available.
DescripciónTrabajo presentado en la 21st International Conference Medical Image Computing and Computer Assisted Intervention, celebrada en Granada, del 16 al 20 de septiembre de 2018
Versión del editorhttps://doi.org/10.1007/978-3-030-00934-2_36
URIhttp://hdl.handle.net/10261/179729
DOI10.1007/978-3-030-00934-2_36
ISBN978-3-030-00933-5
ISSN0302-9743
Aparece en las colecciones: (IRII) Artículos




Ficheros en este ítem:
Fichero Descripción Tamaño Formato
accesoRestringido.pdf15,38 kBAdobe PDFVista previa
Visualizar/Abrir
Mostrar el registro completo

CORE Recommender

Page view(s)

188
checked on 28-mar-2024

Download(s)

23
checked on 28-mar-2024

Google ScholarTM

Check

Altmetric

Altmetric


NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.