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End to End Colonic Content Assessment: ColonMetry Application
The analysis of colonic contents is a valuable tool for the gastroenterologist and has multiple applications in clinical routine. When considering magnetic resonance imaging (MRI) modalities, T2 weighted images are capable of segmenting the colonic lumen, whereas fecal and gas contents can only be d...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10000726/ https://www.ncbi.nlm.nih.gov/pubmed/36900054 http://dx.doi.org/10.3390/diagnostics13050910 |
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author | Orellana, Bernat Monclús, Eva Navazo, Isabel Bendezú, Álvaro Malagelada, Carolina Azpiroz, Fernando |
author_facet | Orellana, Bernat Monclús, Eva Navazo, Isabel Bendezú, Álvaro Malagelada, Carolina Azpiroz, Fernando |
author_sort | Orellana, Bernat |
collection | PubMed |
description | The analysis of colonic contents is a valuable tool for the gastroenterologist and has multiple applications in clinical routine. When considering magnetic resonance imaging (MRI) modalities, T2 weighted images are capable of segmenting the colonic lumen, whereas fecal and gas contents can only be distinguished in T1 weighted images. In this paper, we present an end-to-end quasi-automatic framework that comprises all the steps needed to accurately segment the colon in T2 and T1 images and to extract colonic content and morphology data to provide the quantification of colonic content and morphology data. As a consequence, physicians have gained new insights into the effects of diets and the mechanisms of abdominal distension. |
format | Online Article Text |
id | pubmed-10000726 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100007262023-03-11 End to End Colonic Content Assessment: ColonMetry Application Orellana, Bernat Monclús, Eva Navazo, Isabel Bendezú, Álvaro Malagelada, Carolina Azpiroz, Fernando Diagnostics (Basel) Technical Note The analysis of colonic contents is a valuable tool for the gastroenterologist and has multiple applications in clinical routine. When considering magnetic resonance imaging (MRI) modalities, T2 weighted images are capable of segmenting the colonic lumen, whereas fecal and gas contents can only be distinguished in T1 weighted images. In this paper, we present an end-to-end quasi-automatic framework that comprises all the steps needed to accurately segment the colon in T2 and T1 images and to extract colonic content and morphology data to provide the quantification of colonic content and morphology data. As a consequence, physicians have gained new insights into the effects of diets and the mechanisms of abdominal distension. MDPI 2023-02-28 /pmc/articles/PMC10000726/ /pubmed/36900054 http://dx.doi.org/10.3390/diagnostics13050910 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Technical Note Orellana, Bernat Monclús, Eva Navazo, Isabel Bendezú, Álvaro Malagelada, Carolina Azpiroz, Fernando End to End Colonic Content Assessment: ColonMetry Application |
title | End to End Colonic Content Assessment: ColonMetry Application |
title_full | End to End Colonic Content Assessment: ColonMetry Application |
title_fullStr | End to End Colonic Content Assessment: ColonMetry Application |
title_full_unstemmed | End to End Colonic Content Assessment: ColonMetry Application |
title_short | End to End Colonic Content Assessment: ColonMetry Application |
title_sort | end to end colonic content assessment: colonmetry application |
topic | Technical Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10000726/ https://www.ncbi.nlm.nih.gov/pubmed/36900054 http://dx.doi.org/10.3390/diagnostics13050910 |
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