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New indexes for myofibril linearity in muscle image analysis
The endeavor to evaluate the linearity of myofibrillar structures and their potential deviation from a straight line is a fascinating problem in muscle tissue image analysis. In this Letter, we suggest two different strategies for solving the same challenge. The first strategy is based on an alignme...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PAGEPress Publications, Pavia, Italy
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9830398/ https://www.ncbi.nlm.nih.gov/pubmed/36193819 http://dx.doi.org/10.4081/ejtm.2022.10736 |
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author | Rocchi, Ettore Peluso, Sara Amatori, Stefano Sisti, Davide |
author_facet | Rocchi, Ettore Peluso, Sara Amatori, Stefano Sisti, Davide |
author_sort | Rocchi, Ettore |
collection | PubMed |
description | The endeavor to evaluate the linearity of myofibrillar structures and their potential deviation from a straight line is a fascinating problem in muscle tissue image analysis. In this Letter, we suggest two different strategies for solving the same challenge. The first strategy is based on an alignment index, which could be derived by comparing the sum of the lengths of the individual sarcomeres with the distance between the "head" of the first and the "tail" of the last sarcomere. The second strategy relies on circular statistics, which takes a cue from an already suggested method. Our proposed methods are alternatives: the former has the advantage of simplicity; the latter is certainly more elegant and gives greater substance to statistical analysis, but in contrast, it also has greater computational complexity. |
format | Online Article Text |
id | pubmed-9830398 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PAGEPress Publications, Pavia, Italy |
record_format | MEDLINE/PubMed |
spelling | pubmed-98303982023-01-11 New indexes for myofibril linearity in muscle image analysis Rocchi, Ettore Peluso, Sara Amatori, Stefano Sisti, Davide Eur J Transl Myol Article The endeavor to evaluate the linearity of myofibrillar structures and their potential deviation from a straight line is a fascinating problem in muscle tissue image analysis. In this Letter, we suggest two different strategies for solving the same challenge. The first strategy is based on an alignment index, which could be derived by comparing the sum of the lengths of the individual sarcomeres with the distance between the "head" of the first and the "tail" of the last sarcomere. The second strategy relies on circular statistics, which takes a cue from an already suggested method. Our proposed methods are alternatives: the former has the advantage of simplicity; the latter is certainly more elegant and gives greater substance to statistical analysis, but in contrast, it also has greater computational complexity. PAGEPress Publications, Pavia, Italy 2022-10-04 /pmc/articles/PMC9830398/ /pubmed/36193819 http://dx.doi.org/10.4081/ejtm.2022.10736 Text en https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution Noncommercial License (by-nc 4.0) which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. |
spellingShingle | Article Rocchi, Ettore Peluso, Sara Amatori, Stefano Sisti, Davide New indexes for myofibril linearity in muscle image analysis |
title | New indexes for myofibril linearity in muscle image analysis |
title_full | New indexes for myofibril linearity in muscle image analysis |
title_fullStr | New indexes for myofibril linearity in muscle image analysis |
title_full_unstemmed | New indexes for myofibril linearity in muscle image analysis |
title_short | New indexes for myofibril linearity in muscle image analysis |
title_sort | new indexes for myofibril linearity in muscle image analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9830398/ https://www.ncbi.nlm.nih.gov/pubmed/36193819 http://dx.doi.org/10.4081/ejtm.2022.10736 |
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