From 2dde2a5e3a9c510adad5dd64d0ec6b666fc150ee Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Sth=C3=A9phany=20Karoline=20Soares=20de=20Ara=C3=BAjo=20Te?= =?UTF-8?q?zza?= Date: Wed, 20 Oct 2021 19:13:07 -0300 Subject: [PATCH] Update article info --- .../sistema/cite-us/cite-us.component.html | 157 ++++++++++-------- .../downloads/downloads.component.html | 5 +- 2 files changed, 92 insertions(+), 70 deletions(-) diff --git a/src/app/components/sistema/cite-us/cite-us.component.html b/src/app/components/sistema/cite-us/cite-us.component.html index d685f3d..ab8f142 100644 --- a/src/app/components/sistema/cite-us/cite-us.component.html +++ b/src/app/components/sistema/cite-us/cite-us.component.html @@ -1,71 +1,90 @@ -

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- Rezende, Mariana Trevisan; Tobias, Alessandra Hermógenes Gomes; Silva, Raniere; Oliveira, Paulo; Sombra de Medeiros, Fatima; Ushizima, Daniela; et al. (2020): CRIC Cervix Cell Classification. figshare. Collection. https://doi.org/10.6084/m9.figshare.c.4960286.v2 -
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- Rezende, M. T., et al.. CRIC Cervix Cell Classification. 2, figshare, 1 May 2020, doi:10.6084/m9.figshare.c.4960286.v2. -
-
- Rezende, M. T., Tobias, A. H. G., Silva, R., Oliveira, P., Sombra de Medeiros, F., Ushizima, D., … Bianchi, A. G. C.. (2020). CRIC Cervix Cell Classification. doi: 10.6084/m9.figshare.c.4960286.v2 -
-
- Rezende, Mariana Trevisan, Alessandra Hermógenes Gomes Tobias, Raniere Silva, Paulo Oliveira, Fatima Sombra de Medeiros, Daniela Ushizima, Claudia Martins Carneiro, and Andrea Gomes Campos Bianchi. “CRIC Cervix Cell Classification”. figshare, May 1, 2020. https://doi.org/10.6084/m9.figshare.c.4960286.v2. -
-
- REZENDE, M. T. et al.. CRIC Cervix Cell Classificationfigshare, , 1 maio 2020. . Disponível em: <https://figshare.com/collections/CRIC_Cervix_Cell_Classification/4960286/2>.. Acesso em: {{today.getDate()}}/{{today.getMonth()}}/{{today.getFullYear()}}. -
-
- 
@misc{cric_cervix,
-title="CRIC Cervix Cell Classification",
-url="https://figshare.com/collections/CRIC_Cervix_Cell_Classification/4960286/2",
-DOI="10.6084/m9.figshare.c.4960286.v2",
-abstractNote="400 images from microscope slides of the uterine cervix using the conventional smear (Pap smear) and the epithelial cell abnormalities classified according to Bethesda system. Data visualisation available at http://database.cric.com.br/.",
-publisher="figshare",
-author="Rezende, Mariana Trevisan and Tobias, Alessandra Hermógenes Gomes and Silva, Raniere and Oliveira, Paulo and Sombra de Medeiros, Fatima and Ushizima, Daniela and Carneiro, Claudia Martins and Bianchi, Andrea Gomes Campos",
-year="2020",
-month="May"
-}
-
+ +
+
+

Rezende, Mariana Trevisan; Tobias, Alessandra Hermógenes Gomes; Silva, Raniere; Oliveira, Paulo; Sombra de + Medeiros, Fatima; Ushizima, Daniela; et al. (2020): CRIC Cervix Cell Classification. figshare. Collection. + https://doi.org/10.6084/m9.figshare.c.4960286.v2

+

+ Rezende, Mariana Bianchi; Silva, Raniere; Bernardo, Fagner de Oliveira; Tobias, Alessandra Hermógenes Gomes; Oliveira, Paulo Henrique Calaes; Machado, Tales Gomes; et al. (2021): Cric searchable image database as a public platform for conventional pap smear cytology data. Scientific Data. https://doi.org/10.1038/s41597-021-00933-8 +

+
+

Rezende, M. T., et al.. CRIC Cervix Cell Classification. 2, figshare, 1 May 2020, + doi:10.6084/m9.figshare.c.4960286.v2.

+

Rezende, Mariana T., et al. "Cric searchable image database as a public platform for conventional pap smear + cytology data." Scientific Data 8.1 (2021): 1-8.

+
+
+

Rezende, M. T., Tobias, A. H. G., Silva, R., Oliveira, P., Sombra de Medeiros, F., Ushizima, D., … Bianchi, + A. G. C.. (2020). CRIC Cervix Cell Classification. doi: 10.6084/m9.figshare.c.4960286.v2

+

Rezende, M. T., Silva, R., Bernardo, F. D. O., Tobias, A. H., Oliveira, P. H., Machado, T. M., ... & Bianchi, + A. G. (2021). Cric searchable image database as a public platform for conventional pap smear cytology data. + Scientific Data, 8(1), 1-8.

+
+
+

Rezende, Mariana Trevisan, Alessandra Hermógenes Gomes Tobias, Raniere Silva, Paulo Oliveira, Fatima Sombra + de Medeiros, Daniela Ushizima, Claudia Martins Carneiro, and Andrea Gomes Campos Bianchi. “CRIC Cervix Cell + Classification”. figshare, May 1, 2020. https://doi.org/10.6084/m9.figshare.c.4960286.v2.

+

+ Rezende, Mariana T., Raniere Silva, Fagner de O. Bernardo, Alessandra H. G. Tobias, Paulo H. C. Oliveira, Tales M. Machado, Caio S. Costa, et al. “Cric Searchable Image Database as a Public Platform for Conventional Pap Smear Cytology Data.” Scientific Data 8, no. 1 (June 10, 2021). https://doi.org/10.1038/s41597-021-00933-8. +

+
+
+

REZENDE, M. T. et al. CRIC Cervix Cell Classificationfigshare, 1 maio 2020. Disponível em: + <https://figshare.com/collections/CRIC_Cervix_Cell_Classification/4960286/2>. Acesso em: + {{today.getDate()}}/{{today.getMonth()}}/{{today.getFullYear()}}.

+

+ REZENDE, M. T. et al. Cric searchable image database as a public platform for conventional pap smear cytology data. Scientific Data, v. 8, n. 1, 10 jun. 2021. Disponível em: + <https://www.nature.com/articles/s41597-021-00933-8>. Acesso em: + {{today.getDate()}}/{{today.getMonth()}}/{{today.getFullYear()}}. +

+
+
+ 
+@misc{cric_cervix,
+    title="CRIC Cervix Cell Classification",
+    url="https://figshare.com/collections/CRIC_Cervix_Cell_Classification/4960286/2",
+    DOI="10.6084/m9.figshare.c.4960286.v2",
+    abstractNote="400 images from microscope slides of the uterine cervix using the conventional smear (Pap smear) and the epithelial cell abnormalities classified according to Bethesda system. Data visualisation available at http://database.cric.com.br/.",
+    publisher="figshare",
+    author="Rezende, Mariana Trevisan and Tobias, Alessandra Hermógenes Gomes and Silva, Raniere and Oliveira, Paulo and Sombra de Medeiros, Fatima and Ushizima, Daniela and Carneiro, Claudia Martins and Bianchi, Andrea Gomes Campos",
+    year="2020",
+    month="May"
+}
+@article{rezende2021cric,
+    title="Cric searchable image database as a public platform for conventional pap smear cytology data",
+    author="Rezende, Mariana T and Silva, Raniere and Bernardo, Fagner de O and Tobias, Alessandra HG and Oliveira, Paulo HC and Machado, Tales M and Costa, Caio S and Medeiros, Fatima NS and Ushizima, Daniela M and Carneiro, Claudia M and others",
+    journal="Scientific Data",
+    volume="8",
+    number="1",
+    pages="1--8",
+    year="2021",
+    publisher="Nature Publishing Group"
+}
+
+ +
+
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CRIC Cervix Cell Classification

-->

400 images (with 11534 cells) from microscope slides of the uterine cervix using the conventional smear (Pap smear) and the epithelial cell abnormalities classified according to Bethesda system.

The cells in the CRIC Cervix Classification collection are labeled in six (6) classes: negative for intraepithelial lesion or malignancy (NILM); atypical squamous cells of undetermined significance, possibly non-neoplastic (ASC-US); low-grade squamous cell carcinoma (SCC) intraepithelial lesion (LSIL); atypical squamous cells, cannot exclude a high-grade lesion (ASC-H); high-grade squamous intraepithelial lesion (HSIL); and squamous carcinoma (SC).

+

[1] Cric searchable image database as a public platform for conventional pap smear cytology data + - Mariana T. Rezende, Raniere Silva, Fagner de O. Bernardo, Alessandra H. G. Tobias, Paulo H. C. Oliveira, Tales M. Machado, Caio S. Costa, Fatima N. S. Medeiros, Daniela M. Ushizima, Claudia M. Carneiro and Andrea G. C. Bianchi, published in the Nature in June 2021.

@@ -110,8 +112,9 @@

CRIC Cervix Cell Classification - Cropped Image

The CRIC Cervical Cell Classification – Cropped Image (CRIC- CI) was designed to push state of the art in cervical cell classification using cropped patches around nuclei for machine learning algorithm. The database is part of the Cervix Cell classification collection, the bounding boxes of 90 x 90 pixels around nuclei were chosen from different classes. - This dataset divides cells into two more group classes: two class groups and three class groups [1].

+ This dataset divides cells into (3) three group classes: two class, three classes and six class groups [1].

[1] A deep learning ensemble method to assist cytopathologists in the Pap test images classification - Débora N. Diniz, Mariana T. Rezende, Andrea G. C. Bianchi, Claudia M.Carneiro, Eduardo J. S. Luz, Gladston J. P. Moreira, Daniela M. Ushizima, Fátima N. S. de Medeiros, and Marcone J. F. Souza, published in the Journal of Imaging in July 2021.

+

The code from the above article can be found on the GitHub versioning system: https://github.com/debnasser/deep-learning-ensemble-jimaging/blob/main/balance.py.