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Image microarrays (IMA): Digital pathology's missing tool
INTRODUCTION: The increasing availability of whole slide imaging (WSI) data sets (digital slides) from glass slides offers new opportunities for the development of computer-aided diagnostic (CAD) algorithms. With the all-digital pathology workflow that these data sets will enable in the near future,...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3237063/ https://www.ncbi.nlm.nih.gov/pubmed/22200030 http://dx.doi.org/10.4103/2153-3539.86829 |
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author | Hipp, Jason Cheng, Jerome Pantanowitz, Liron Hewitt, Stephen Yagi, Yukako Monaco, James Madabhushi, Anant Rodriguez-canales, Jaime Hanson, Jeffrey Roy-Chowdhuri, Sinchita Filie, Armando C. Feldman, Michael D. Tomaszewski, John E. Shih, Natalie NC. Brodsky, Victor Giaccone, Giuseppe Emmert-Buck, Michael R. Balis, Ulysses J. |
author_facet | Hipp, Jason Cheng, Jerome Pantanowitz, Liron Hewitt, Stephen Yagi, Yukako Monaco, James Madabhushi, Anant Rodriguez-canales, Jaime Hanson, Jeffrey Roy-Chowdhuri, Sinchita Filie, Armando C. Feldman, Michael D. Tomaszewski, John E. Shih, Natalie NC. Brodsky, Victor Giaccone, Giuseppe Emmert-Buck, Michael R. Balis, Ulysses J. |
author_sort | Hipp, Jason |
collection | PubMed |
description | INTRODUCTION: The increasing availability of whole slide imaging (WSI) data sets (digital slides) from glass slides offers new opportunities for the development of computer-aided diagnostic (CAD) algorithms. With the all-digital pathology workflow that these data sets will enable in the near future, literally millions of digital slides will be generated and stored. Consequently, the field in general and pathologists, specifically, will need tools to help extract actionable information from this new and vast collective repository. METHODS: To address this limitation, we designed and implemented a tool (dCORE) to enable the systematic capture of image tiles with constrained size and resolution that contain desired histopathologic features. RESULTS: In this communication, we describe a user-friendly tool that will enable pathologists to mine digital slides archives to create image microarrays (IMAs). IMAs are to digital slides as tissue microarrays (TMAs) are to cell blocks. Thus, a single digital slide could be transformed into an array of hundreds to thousands of high quality digital images, with each containing key diagnostic morphologies and appropriate controls. Current manual digital image cut-and-paste methods that allow for the creation of a grid of images (such as an IMA) of matching resolutions are tedious. CONCLUSION: The ability to create IMAs representing hundreds to thousands of vetted morphologic features has numerous applications in education, proficiency testing, consensus case review, and research. Lastly, in a manner analogous to the way conventional TMA technology has significantly accelerated in situ studies of tissue specimens use of IMAs has similar potential to significantly accelerate CAD algorithm development. |
format | Online Article Text |
id | pubmed-3237063 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-32370632011-12-23 Image microarrays (IMA): Digital pathology's missing tool Hipp, Jason Cheng, Jerome Pantanowitz, Liron Hewitt, Stephen Yagi, Yukako Monaco, James Madabhushi, Anant Rodriguez-canales, Jaime Hanson, Jeffrey Roy-Chowdhuri, Sinchita Filie, Armando C. Feldman, Michael D. Tomaszewski, John E. Shih, Natalie NC. Brodsky, Victor Giaccone, Giuseppe Emmert-Buck, Michael R. Balis, Ulysses J. J Pathol Inform Original Article INTRODUCTION: The increasing availability of whole slide imaging (WSI) data sets (digital slides) from glass slides offers new opportunities for the development of computer-aided diagnostic (CAD) algorithms. With the all-digital pathology workflow that these data sets will enable in the near future, literally millions of digital slides will be generated and stored. Consequently, the field in general and pathologists, specifically, will need tools to help extract actionable information from this new and vast collective repository. METHODS: To address this limitation, we designed and implemented a tool (dCORE) to enable the systematic capture of image tiles with constrained size and resolution that contain desired histopathologic features. RESULTS: In this communication, we describe a user-friendly tool that will enable pathologists to mine digital slides archives to create image microarrays (IMAs). IMAs are to digital slides as tissue microarrays (TMAs) are to cell blocks. Thus, a single digital slide could be transformed into an array of hundreds to thousands of high quality digital images, with each containing key diagnostic morphologies and appropriate controls. Current manual digital image cut-and-paste methods that allow for the creation of a grid of images (such as an IMA) of matching resolutions are tedious. CONCLUSION: The ability to create IMAs representing hundreds to thousands of vetted morphologic features has numerous applications in education, proficiency testing, consensus case review, and research. Lastly, in a manner analogous to the way conventional TMA technology has significantly accelerated in situ studies of tissue specimens use of IMAs has similar potential to significantly accelerate CAD algorithm development. Medknow Publications & Media Pvt Ltd 2011-10-29 /pmc/articles/PMC3237063/ /pubmed/22200030 http://dx.doi.org/10.4103/2153-3539.86829 Text en Copyright: © 2011 Hipp J. http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Original Article Hipp, Jason Cheng, Jerome Pantanowitz, Liron Hewitt, Stephen Yagi, Yukako Monaco, James Madabhushi, Anant Rodriguez-canales, Jaime Hanson, Jeffrey Roy-Chowdhuri, Sinchita Filie, Armando C. Feldman, Michael D. Tomaszewski, John E. Shih, Natalie NC. Brodsky, Victor Giaccone, Giuseppe Emmert-Buck, Michael R. Balis, Ulysses J. Image microarrays (IMA): Digital pathology's missing tool |
title | Image microarrays (IMA): Digital pathology's missing tool |
title_full | Image microarrays (IMA): Digital pathology's missing tool |
title_fullStr | Image microarrays (IMA): Digital pathology's missing tool |
title_full_unstemmed | Image microarrays (IMA): Digital pathology's missing tool |
title_short | Image microarrays (IMA): Digital pathology's missing tool |
title_sort | image microarrays (ima): digital pathology's missing tool |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3237063/ https://www.ncbi.nlm.nih.gov/pubmed/22200030 http://dx.doi.org/10.4103/2153-3539.86829 |
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