Analysis of pancreas histological images for glucose intolerance identificationusing ImageJ-preliminary results
| Main Author: | |
|---|---|
| Publication Date: | 2013 |
| Other Authors: | , , |
| Format: | Article |
| Language: | eng |
| Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Download full: | http://hdl.handle.net/10174/9927 https://doi.org/10.1201/b15810-56 |
Summary: | The observation in microscopy of histological sections allows us to evaluate structural differences, in pancreatic cells, between rats with normal glucose tolerance and with glucose intolerance (pre-diabetic) situation. Nevertheless, this pre-diabetic condition implies subtle changes in islets of Langerhans structure. This and the normal variability among sampled cells makes difficult the task of identifying glucose intolerance (pre-diabetic situation) with a low level of error. This paper presents preliminary results in the processing of histological pancreas images with the goal of identifying pre-diabetic situation in Wistar rats. The immediate goal of this work is to evaluate the performance of a classifier based in a morphometric measurement of the histological images and to assess the potential for image based automatic processing and classification. A set of 90 images, were used (58 from rats with normal glucose tolerance, and 32 from pre-diabetic ones). These images were segmented manually using ImageJ. This segmentation and area measurements have been speedup by the application of ImageJ macros which were defined for this purpose. The ratio, between the area of -cells and the islets of Langerhans , was used has the indicator of the prediabetic situation. Considering this feature, a receiver operating characteristic analysis has been performed. True positive rate, vs. false positive rate shows the predicted performance of a binary classifier as its discrimination threshold is varied. |
| id |
RCAP_1efe129e123e455028b15f993bcdc68f |
|---|---|
| oai_identifier_str |
oai:dspace.uevora.pt:10174/9927 |
| network_acronym_str |
RCAP |
| network_name_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| repository_id_str |
https://opendoar.ac.uk/repository/7160 |
| spelling |
Analysis of pancreas histological images for glucose intolerance identificationusing ImageJ-preliminary resultsAnalysis of Histological ImagesPancreasGlucose IntoleranceImageJThe observation in microscopy of histological sections allows us to evaluate structural differences, in pancreatic cells, between rats with normal glucose tolerance and with glucose intolerance (pre-diabetic) situation. Nevertheless, this pre-diabetic condition implies subtle changes in islets of Langerhans structure. This and the normal variability among sampled cells makes difficult the task of identifying glucose intolerance (pre-diabetic situation) with a low level of error. This paper presents preliminary results in the processing of histological pancreas images with the goal of identifying pre-diabetic situation in Wistar rats. The immediate goal of this work is to evaluate the performance of a classifier based in a morphometric measurement of the histological images and to assess the potential for image based automatic processing and classification. A set of 90 images, were used (58 from rats with normal glucose tolerance, and 32 from pre-diabetic ones). These images were segmented manually using ImageJ. This segmentation and area measurements have been speedup by the application of ImageJ macros which were defined for this purpose. The ratio, between the area of -cells and the islets of Langerhans , was used has the indicator of the prediabetic situation. Considering this feature, a receiver operating characteristic analysis has been performed. True positive rate, vs. false positive rate shows the predicted performance of a binary classifier as its discrimination threshold is varied.CRC Press2014-01-23T10:10:11Z2014-01-232013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/9927http://hdl.handle.net/10174/9927https://doi.org/10.1201/b15810-56engRato LM, Capela e Silva F, Costa AR, Antunes CM. (2013) Analysis of pancreas histological images for glucose intolerance identificationusing ImageJ-preliminary results. Computational Vision and Medical Image Processing IV, VIPIMAGE 2013. Edited by João Manuel R. S. Tavares and R.M. Natal Jorge. CRC Press 2013, pp: 319–322.319-322978-1-138-00081-0eBook ISBN 978-1-315-81292-2http://www.crcnetbase.com/doi/abs/10.1201/b15810-56Departamento de Informática, Departamento de Química, ICAAM-Instituto de Ciências Agrárias e Ambientais Mediterrânicaslmr@uevora.ptfcs@uevora.ptacrc@uevora.ptcmma@uevora.pt283Rato, L.M.Capela e Silva, F.Costa, A.R.Antunes, C.M.info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-01-03T18:52:21Zoai:dspace.uevora.pt:10174/9927Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T12:00:35.958369Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
Analysis of pancreas histological images for glucose intolerance identificationusing ImageJ-preliminary results |
| title |
Analysis of pancreas histological images for glucose intolerance identificationusing ImageJ-preliminary results |
| spellingShingle |
Analysis of pancreas histological images for glucose intolerance identificationusing ImageJ-preliminary results Rato, L.M. Analysis of Histological Images Pancreas Glucose Intolerance ImageJ |
| title_short |
Analysis of pancreas histological images for glucose intolerance identificationusing ImageJ-preliminary results |
| title_full |
Analysis of pancreas histological images for glucose intolerance identificationusing ImageJ-preliminary results |
| title_fullStr |
Analysis of pancreas histological images for glucose intolerance identificationusing ImageJ-preliminary results |
| title_full_unstemmed |
Analysis of pancreas histological images for glucose intolerance identificationusing ImageJ-preliminary results |
| title_sort |
Analysis of pancreas histological images for glucose intolerance identificationusing ImageJ-preliminary results |
| author |
Rato, L.M. |
| author_facet |
Rato, L.M. Capela e Silva, F. Costa, A.R. Antunes, C.M. |
| author_role |
author |
| author2 |
Capela e Silva, F. Costa, A.R. Antunes, C.M. |
| author2_role |
author author author |
| dc.contributor.author.fl_str_mv |
Rato, L.M. Capela e Silva, F. Costa, A.R. Antunes, C.M. |
| dc.subject.por.fl_str_mv |
Analysis of Histological Images Pancreas Glucose Intolerance ImageJ |
| topic |
Analysis of Histological Images Pancreas Glucose Intolerance ImageJ |
| description |
The observation in microscopy of histological sections allows us to evaluate structural differences, in pancreatic cells, between rats with normal glucose tolerance and with glucose intolerance (pre-diabetic) situation. Nevertheless, this pre-diabetic condition implies subtle changes in islets of Langerhans structure. This and the normal variability among sampled cells makes difficult the task of identifying glucose intolerance (pre-diabetic situation) with a low level of error. This paper presents preliminary results in the processing of histological pancreas images with the goal of identifying pre-diabetic situation in Wistar rats. The immediate goal of this work is to evaluate the performance of a classifier based in a morphometric measurement of the histological images and to assess the potential for image based automatic processing and classification. A set of 90 images, were used (58 from rats with normal glucose tolerance, and 32 from pre-diabetic ones). These images were segmented manually using ImageJ. This segmentation and area measurements have been speedup by the application of ImageJ macros which were defined for this purpose. The ratio, between the area of -cells and the islets of Langerhans , was used has the indicator of the prediabetic situation. Considering this feature, a receiver operating characteristic analysis has been performed. True positive rate, vs. false positive rate shows the predicted performance of a binary classifier as its discrimination threshold is varied. |
| publishDate |
2013 |
| dc.date.none.fl_str_mv |
2013-01-01T00:00:00Z 2014-01-23T10:10:11Z 2014-01-23 |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/9927 http://hdl.handle.net/10174/9927 https://doi.org/10.1201/b15810-56 |
| url |
http://hdl.handle.net/10174/9927 https://doi.org/10.1201/b15810-56 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
Rato LM, Capela e Silva F, Costa AR, Antunes CM. (2013) Analysis of pancreas histological images for glucose intolerance identificationusing ImageJ-preliminary results. Computational Vision and Medical Image Processing IV, VIPIMAGE 2013. Edited by João Manuel R. S. Tavares and R.M. Natal Jorge. CRC Press 2013, pp: 319–322. 319-322 978-1-138-00081-0 eBook ISBN 978-1-315-81292-2 http://www.crcnetbase.com/doi/abs/10.1201/b15810-56 Departamento de Informática, Departamento de Química, ICAAM-Instituto de Ciências Agrárias e Ambientais Mediterrânicas lmr@uevora.pt fcs@uevora.pt acrc@uevora.pt cmma@uevora.pt 283 |
| dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
| eu_rights_str_mv |
openAccess |
| dc.publisher.none.fl_str_mv |
CRC Press |
| publisher.none.fl_str_mv |
CRC Press |
| dc.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
| instname_str |
FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
| instacron_str |
RCAAP |
| institution |
RCAAP |
| reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| collection |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| repository.name.fl_str_mv |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
| repository.mail.fl_str_mv |
info@rcaap.pt |
| _version_ |
1833592429234618368 |