Literature DB >> 21342753

Microscopic image analysis for quantitative characterization of muscle fiber type composition.

Olcay Sertel1, Belma Dogdas, Chi Sung Chiu, Metin N Gurcan.   

Abstract

Skeletal muscles consist of muscle fibers that are responsible for contracting and generating force. Skeletal muscle fibers are categorized into distinct subtypes based on several characteristics such as contraction time, force production and resistance to fatigue. The composition of distinct muscle fibers in terms of their number and cross-sectional areas is characterized by a histological examination. However, manual delineation of individual muscle fibers from digitized muscle histology tissue sections is extremely time-consuming. In this study, we propose an automated image analysis system for quantitative characterization of muscle fiber type composition. The proposed system operates on digitized histological muscle tissue slides and consists of the following steps: segmentation of muscle fibers, registration of successive slides with distinct stains, and classification of muscle fibers into distinct subtypes. The performance of the proposed approach was tested on a dataset consisting of 25 image pairs of successive muscle histological cross-sections with different ATPase stain. Experimental results demonstrate a promising overall segmentation and classification accuracy of 89.1% in identifying muscle fibers of distinct subtypes.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21342753     DOI: 10.1016/j.compmedimag.2011.01.009

Source DB:  PubMed          Journal:  Comput Med Imaging Graph        ISSN: 0895-6111            Impact factor:   4.790


  9 in total

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Authors:  Ye Li; Zhong Yang; Yaming Wang; Xinhua Cao; Xiaoyin Xu
Journal:  Comput Biol Med       Date:  2018-11-12       Impact factor: 4.589

3.  Automatic Myonuclear Detection in Isolated Single Muscle Fibers Using Robust Ellipse Fitting and Sparse Representation.

Authors:  Hai Su; Fuyong Xing; Jonah D Lee; Charlotte A Peterson; Lin Yang
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2014 Jul-Aug       Impact factor: 3.710

4.  Automatic and unbiased segmentation and quantification of myofibers in skeletal muscle.

Authors:  Ariel Waisman; Alessandra Marie Norris; Martín Elías Costa; Daniel Kopinke
Journal:  Sci Rep       Date:  2021-06-03       Impact factor: 4.379

5.  Soft texture of atlantic salmon fillets is associated with glycogen accumulation.

Authors:  Jacob S Torgersen; Erling Olaf Koppang; Lars H Stien; Achim Kohler; Mona E Pedersen; Turid Mørkøre
Journal:  PLoS One       Date:  2014-01-09       Impact factor: 3.240

6.  Myofibre segmentation in H&E stained adult skeletal muscle images using coherence-enhancing diffusion filtering.

Authors:  Harry Strange; Ian Scott; Reyer Zwiggelaar
Journal:  BMC Med Imaging       Date:  2014-10-29       Impact factor: 1.930

7.  MuscleJ: a high-content analysis method to study skeletal muscle with a new Fiji tool.

Authors:  Alicia Mayeuf-Louchart; David Hardy; Quentin Thorel; Pascal Roux; Lorna Gueniot; David Briand; Aurélien Mazeraud; Adrien Bouglé; Spencer L Shorte; Bart Staels; Fabrice Chrétien; Hélène Duez; Anne Danckaert
Journal:  Skelet Muscle       Date:  2018-08-06       Impact factor: 4.912

Review 8.  Computational pathology for musculoskeletal conditions using machine learning: advances, trends, and challenges.

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9.  Automatic Detection of Medial and Lateral Compartments from Histological Sections of Mouse Knee Joints Using the Single-Shot Multibox Detector Algorithm.

Authors:  Yoshifumi Mori; Takeshi Oichi; Motomi Enomoto-Iwamoto; Taku Saito
Journal:  Cartilage       Date:  2022 Jan-Mar       Impact factor: 3.117

  9 in total

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