Tipo
Artigos em Revista
Tipo de Documento
Artigo Completo
Título
Case study – apply a deep-learning algorithm to exosomes detection with online resources
Participantes na publicação
M. C. Proença (Author)
MARE – Marine and Environmental Sciences Centre, Universidade de Lisboa
Dep. Física
A. P. Alves de Matos (Author)
EGAS MONIZ - COOPERATIVA DE ENSINO SUPERIOR, CRL
Resumo
Abstract - exosomes are membrane vesicles part of the extracellular vesicle structures (EVs) that constitute a mode of intercellular communication. Extracellular vesicles are promising biomarkers for many diseases. Their participation in pathological processes, with relevance to non-communicable diseases (NCDs) is supported by mounting evidence and their study will surely drive new therapeutic and diagnostic strategies. Electron microscopy is currently used to identify this kind of particles in transmission electron microscopy images, but their morphology can span a wide range of vesicle structures and sizes. This preliminary work shows how a recent deep-learning algorithm available online can be applied to exosome images to localize all the instances of the objects of interest, in any scale and several backgrounds, allowing an in-depth analysis of their composition, and adding a novel instrument for their morphological classification.
Data de Publicação
2021-12-24
Instituição
FACULDADE DE CIÊNCIAS DA UNIVERSIDADE DE LISBOA
Suporte
Annals of Antivirals and Antiretrovirals
Identificadores da Publicação
ISSN - 2692-4625
Editora
Peertechz Publications Private Limited
Número de Páginas
3
Página Inicial
033
Página Final
035
Identificadores do Documento
DOI -
https://doi.org/10.17352/aaa.000014
URL -
http://dx.doi.org/10.17352/aaa.000014
Keywords
Exosomes; TEM images; Deep-learning algorithms; Detection of small objects