Single-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencoders
Q2
- Autores:
-
Mendoza-Léon, Ricardo
Puentes, John
Uriza Carrasco, Luis Felipe
Hernández Hoyos, Marcela
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2020
- Institución:
- Pontificia Universidad Javeriana
- Repositorio:
- Repositorio Universidad Javeriana
- Idioma:
- eng
- OAI Identifier:
- oai:repository.javeriana.edu.co:10554/53823
- Acceso en línea:
- https://www.sciencedirect.com/science/article/pii/S0010482519303865?via%3Dihub
http://hdl.handle.net/10554/53823
https://doi.org/10.1016/j.compbiomed.2019.103527
- Palabra clave:
- Alzheimer disease
Supervised autoencoder
Supervised switching autoencoder
Convolutional neural networks
Representation learning
Magnetic resonance imaging
- Rights
- License
- Atribución-NoComercial 4.0 Internacional
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| dc.title.spa.fl_str_mv |
Single-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencoders |
| title |
Single-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencoders |
| spellingShingle |
Single-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencoders Alzheimer disease Supervised autoencoder Supervised switching autoencoder Convolutional neural networks Representation learning Magnetic resonance imaging |
| title_short |
Single-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencoders |
| title_full |
Single-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencoders |
| title_fullStr |
Single-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencoders |
| title_full_unstemmed |
Single-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencoders |
| title_sort |
Single-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencoders |
| dc.creator.fl_str_mv |
Mendoza-Léon, Ricardo Puentes, John Uriza Carrasco, Luis Felipe Hernández Hoyos, Marcela |
| dc.contributor.author.none.fl_str_mv |
Mendoza-Léon, Ricardo Puentes, John Uriza Carrasco, Luis Felipe Hernández Hoyos, Marcela |
| dc.contributor.corporatename.none.fl_str_mv |
Pontificia Universidad Javeriana. Facultad de Medicina. Departamento de Radiología e Imágenes Diagnósticas Pontificia Universidad Javeriana. Facultad de Medicina. Hospital Universitario San Ignacio |
| dc.subject.keyword.spa.fl_str_mv |
Alzheimer disease Supervised autoencoder Supervised switching autoencoder Convolutional neural networks Representation learning Magnetic resonance imaging |
| topic |
Alzheimer disease Supervised autoencoder Supervised switching autoencoder Convolutional neural networks Representation learning Magnetic resonance imaging |
| description |
Q2 |
| publishDate |
2020 |
| dc.date.created.none.fl_str_mv |
2020 |
| dc.date.accessioned.none.fl_str_mv |
2021-05-10T22:26:35Z |
| dc.date.available.none.fl_str_mv |
2021-05-10T22:26:35Z |
| dc.type.local.spa.fl_str_mv |
Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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https://www.sciencedirect.com/science/article/pii/S0010482519303865?via%3Dihub |
| dc.identifier.issn.spa.fl_str_mv |
0010-4825 /1879-0534 |
| dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/10554/53823 |
| dc.identifier.doi.spa.fl_str_mv |
https://doi.org/10.1016/j.compbiomed.2019.103527 |
| dc.identifier.instname.spa.fl_str_mv |
instname:Pontificia Universidad Javeriana |
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reponame:Repositorio Institucional - Pontificia Universidad Javeriana |
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repourl:https://repository.javeriana.edu.co |
| url |
https://www.sciencedirect.com/science/article/pii/S0010482519303865?via%3Dihub http://hdl.handle.net/10554/53823 https://doi.org/10.1016/j.compbiomed.2019.103527 |
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0010-4825 /1879-0534 instname:Pontificia Universidad Javeriana reponame:Repositorio Institucional - Pontificia Universidad Javeriana repourl:https://repository.javeriana.edu.co |
| dc.language.iso.spa.fl_str_mv |
eng |
| language |
eng |
| dc.relation.citationstartpage.spa.fl_str_mv |
1 |
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14 |
| dc.relation.ispartofjournal.spa.fl_str_mv |
Computers in Biology and Medicine |
| dc.relation.citationvolume.spa.fl_str_mv |
116 |
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Atribución-NoComercial 4.0 Internacional |
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http://creativecommons.org/licenses/by-nc/4.0/ |
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http://purl.org/coar/access_right/c_abf2 |
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Atribución-NoComercial 4.0 Internacional http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
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PDF |
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application/pdf |
| institution |
Pontificia Universidad Javeriana |
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http://repository.javeriana.edu.co/bitstream/10554/53823/1/Single-slice%20Alzheimer%27s%20disease%20classification%20and%20disease%20regional%20analysis%20with%20supervised%20switching%20autoencoders.pdf http://repository.javeriana.edu.co/bitstream/10554/53823/2/license.txt http://repository.javeriana.edu.co/bitstream/10554/53823/3/Single-slice%20Alzheimer%27s%20disease%20classification%20and%20disease%20regional%20analysis%20with%20supervised%20switching%20autoencoders.pdf.jpg |
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Atribución-NoComercial 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc/4.0/http://purl.org/coar/access_right/c_abf2Mendoza-Léon, RicardoPuentes, JohnUriza Carrasco, Luis FelipeHernández Hoyos, MarcelaPontificia Universidad Javeriana. Facultad de Medicina. Departamento de Radiología e Imágenes DiagnósticasPontificia Universidad Javeriana. Facultad de Medicina. Hospital Universitario San Ignacio2021-05-10T22:26:35Z2021-05-10T22:26:35Z2020https://www.sciencedirect.com/science/article/pii/S0010482519303865?via%3Dihub0010-4825 /1879-0534http://hdl.handle.net/10554/53823https://doi.org/10.1016/j.compbiomed.2019.103527instname:Pontificia Universidad Javerianareponame:Repositorio Institucional - Pontificia Universidad Javerianarepourl:https://repository.javeriana.edu.coPDFapplication/pdfengSingle-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencodersArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1Q2Q2Background Alzheimer's disease (AD) is a difficult to diagnose pathology of the brain that progressively impairs cognitive functions. Computer-assisted diagnosis of AD based on image analysis is an emerging tool to support AD diagnosis. In this article, we explore the application of Supervised Switching Autoencoders (SSAs) to perform AD classification using only one structural Magnetic Resonance Imaging (sMRI) slice. SSAs are revised supervised autoencoder architectures, combining unsupervised representation and supervised classification as one unified model. In this work, we study the capabilities of SSAs to capture complex visual neurodegeneration patterns, and fuse disease semantics simultaneously. We also examine how regions associated to disease state can be discovered by SSAs following a local patch-based approach. Results Our experiments employing a single 2D T1-w sMRI slice per subject show that SSAs perform similarly to previous proposals that rely on full volumetric information and feature-engineered representations. SSAs classification accuracy on slices extracted along the Axial, Coronal, and Sagittal anatomical planes from a balanced cohort of 40 independent test subjects was 87.5%, 90.0%, and 90.0%, respectively. A top sensitivity of 95.0% on both Coronal and Sagittal planes was also obtained. Conclusions SSAs provided well-ranked accuracy performance among previous classification proposals, including feature-engineered and feature learning based methods, using only one scan slice per subject, instead of the whole 3D volume, as it is conventionally done. In addition, regions identified as relevant by SSAs’ were, in most part, coherent or partially coherent in regard to relevant regions reported on previous works. These regions were also associated with findings from medical knowledge, which gives value to our methodology as a potential analytical aid for disease understanding.Revista Internacional - IndexadaAlzheimer diseaseSupervised autoencoderSupervised switching autoencoderConvolutional neural networksRepresentation learningMagnetic resonance imaging114Computers in Biology and Medicine116ORIGINALSingle-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencoders.pdfSingle-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencoders.pdfArtículoapplication/pdf1777826http://repository.javeriana.edu.co/bitstream/10554/53823/1/Single-slice%20Alzheimer%27s%20disease%20classification%20and%20disease%20regional%20analysis%20with%20supervised%20switching%20autoencoders.pdfbb95e82713415d4c30d7b7432646dc01MD51embargoed access|||9999-05-09LICENSElicense.txtlicense.txttext/plain; charset=utf-82603http://repository.javeriana.edu.co/bitstream/10554/53823/2/license.txt2070d280cc89439d983d9eee1b17df53MD52open accessTHUMBNAILSingle-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencoders.pdf.jpgSingle-slice Alzheimer's disease classification and disease regional analysis with supervised switching autoencoders.pdf.jpgIM Thumbnailimage/jpeg9675http://repository.javeriana.edu.co/bitstream/10554/53823/3/Single-slice%20Alzheimer%27s%20disease%20classification%20and%20disease%20regional%20analysis%20with%20supervised%20switching%20autoencoders.pdf.jpg2e69d0a80e1b9e4b7aec9ae6e1887915MD53open access10554/53823oai:repository.javeriana.edu.co:10554/538232023-03-21 10:46:51.549Repositorio Institucional - Pontificia Universidad Javerianarepositorio@javeriana.edu.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 |