scholarly journals Approach for semi-automated measurement of fiber diameter in murine and canine skeletal muscle

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243163
Author(s):  
Courtney R. Stevens ◽  
Josh Berenson ◽  
Michael Sledziona ◽  
Timothy P. Moore ◽  
Lynn Dong ◽  
...  
Keyword(s):  
Cross Sections ◽  
Anisotropic Diffusion ◽  
Fiber Diameter ◽  
Software Tool ◽  
Detection Algorithm ◽  
Analysis Tool ◽  
Diffusion Filtering ◽  
Average Accuracy ◽  
Imagej Software ◽  
Validation Tests

Currently available software tools for automated segmentation and analysis of muscle cross-section images often perform poorly in cases of weak or non-uniform staining conditions. To address these issues, our group has developed the MyoSAT (Myofiber Segmentation and Analysis Tool) image-processing pipeline. MyoSAT combines several unconventional approaches including advanced background leveling, Perona-Malik anisotropic diffusion filtering, and Steger’s line detection algorithm to aid in pre-processing and enhancement of the muscle image. Final segmentation is based upon marker-based watershed segmentation. Validation tests using collagen V labeled murine and canine muscle tissue demonstrate that MyoSAT can determine mean muscle fiber diameter with an average accuracy of ~92.4%. The software has been tested to work on full muscle cross-sections and works well even under non-optimal staining conditions. The MyoSAT software tool has been implemented as a macro for the freely available ImageJ software platform. This new segmentation tool allows scientists to efficiently analyze large muscle cross-sections for use in research studies and diagnostics.

scholarly journals Approach for Semi-Automated Measurement of Fiber Diameter in Murine and Canine Skeletal Muscle

2019 ◽  
Author(s):  
Courtney R. Stevens ◽  
Michael Sledziona ◽  
Timothy P. Moore ◽  
Lynn Dong ◽  
Jonathan Cheetham
Keyword(s):  
Cross Sections ◽  
Anisotropic Diffusion ◽  
Fiber Diameter ◽  
Software Tool ◽  
Detection Algorithm ◽  
Analysis Tool ◽  
Diffusion Filtering ◽  
Average Accuracy ◽  
Imagej Software ◽  
Validation Tests

AbstractCurrently available software tools for automated segmentation and analysis of muscle cross-section images often perform poorly in cases of weak or non-uniform staining conditions. To address these issues, our group has developed the MyoSAT (Myofiber Segmentation and Analysis Tool) image-processing pipeline.MyoSAT combines several unconventional approaches including advanced background leveling, Perona-Malik anisotropic diffusion filtering, and Steger’s line detection algorithm to aid in pre-processing and enhancement of the muscle image. Final segmentation is based upon marker-based watershed segmentation.Validation tests using collagen V labeled murine and canine muscle tissue demonstrate that MyoSAT can determine mean muscle fiber diameter with an average accuracy of ~97%. The software has been tested to work on full muscle cross-sections and works well even under non-optimal staining conditions.The MyoSAT software tool has been implemented as a macro for the freely available ImageJ software platform. This new segmentation tool allows scientists to efficiently analyze large muscle cross-sections for use in research studies and diagnostics.

scholarly journals TriPOINT: a software tool to prioritize important genes in pathways and their non-coding regulators

2018 ◽  
Vol 35 (15) ◽  
pp. 2686-2689
Author(s):  
Asa Thibodeau ◽  
Dong-Guk Shin
Keyword(s):  
Gene Expression ◽  
Software Tool ◽  
Supplementary Information ◽  
Analysis Tool ◽  
Graph Representations ◽  
Expression Levels ◽  
Conducting Pathway ◽  
Pathway Analysis Tool ◽  
Pathway Analyses ◽  
Gene Expression Levels

Abstract Summary Current approaches for pathway analyses focus on representing gene expression levels on graph representations of pathways and conducting pathway enrichment among differentially expressed genes. However, gene expression levels by themselves do not reflect the overall picture as non-coding factors play an important role to regulate gene expression. To incorporate these non-coding factors into pathway analyses and to systematically prioritize genes in a pathway we introduce a new software: Triangulation of Perturbation Origins and Identification of Non-Coding Targets. Triangulation of Perturbation Origins and Identification of Non-Coding Targets is a pathway analysis tool, implemented in Java that identifies the significance of a gene under a condition (e.g. a disease phenotype) by studying graph representations of pathways, analyzing upstream and downstream gene interactions and integrating non-coding regions that may be regulating gene expression levels. Availability and implementation The TriPOINT open source software is freely available at https://github.uconn.edu/ajt06004/TriPOINT under the GPL v3.0 license. Supplementary information Supplementary data are available at Bioinformatics online.

Automated Three-Dimensional Reconstruction of the Left Ventricle From Multiple-Axis Echocardiography

2015 ◽  
Vol 138 (1) ◽  
Author(s):  
Navaneetha Krishnan Rajan ◽  
Zeying Song ◽  
Kenneth R. Hoffmann ◽  
Marek Belohlavek ◽  
Eileen M. McMahon ◽  
...  
Keyword(s):  
Left Ventricle ◽  
Cross Sections ◽  
Low Cost ◽  
Software Tool ◽  
Acquisition Time ◽  
Lv Function ◽  
High Temporal Resolution ◽  
Standard Format ◽  
Flow Simulations ◽  
Automated Method

Two-dimensional echocardiography (echo) is the method of choice for noninvasive evaluation of the left ventricle (LV) function owing to its low cost, fast acquisition time, and high temporal resolution. However, it only provides the LV boundaries in discrete 2D planes, and the 3D LV geometry needs to be reconstructed from those planes to quantify LV wall motion, acceleration, and strain, or to carry out flow simulations. An automated method is developed for the reconstruction of the 3D LV endocardial surface using echo from a few standard cross sections, in contrast with the previous work that has used a series of 2D scans in a linear or rotational manner for 3D reconstruction. The concept is based on a generalized approach so that the number or type (long-axis (LA) or short-axis (SA)) of sectional data is not constrained. The location of the cross sections is optimized to minimize the difference between the reconstructed and measured cross sections, and the reconstructed LV surface is meshed in a standard format. Temporal smoothing is implemented to smooth the motion of the LV and the flow rate. This software tool can be used with existing clinical 2D echo systems to reconstruct the 3D LV geometry and motion to quantify the regional akinesis/dyskinesis, 3D strain, acceleration, and velocities, or to be used in ventricular flow simulations.

Anisotropic diffusion filtering for correlated multiple-coil MRI

2013 ◽  
Author(s):  
Gonzalo Vegas-Sanchez-Ferrero ◽  
Gabriel Ramos-Llorden ◽  
Rodrigo de Luis-Garcia ◽  
Antonio Tristan-Vega ◽  
Santiago Aja-Fernandez
Keyword(s):  
Anisotropic Diffusion ◽  
Diffusion Filtering

A Comparison of Ultrasound Echo Intensity to MRI as a Metric for Tongue Fat Evaluation

SLEEP ◽  
2021 ◽  
Author(s):  
Jason L Yu ◽  
Andrew Wiemken ◽  
Susan M Schultz ◽  
Brendan T Keenan ◽  
Chandra M Sehgal ◽  
...  
Keyword(s):  
Cross Sections ◽  
Ex Vivo ◽  
Human Subjects ◽  
Apnea Hypopnea Index ◽  
Echo Intensity ◽  
Fat Percentage ◽  
Obstructive Sleep ◽  
Imagej Software ◽  
Fat Volume ◽  
Posterior Tongue

Abstract Study Objectives Tongue fat is associated with obstructive sleep apnea (OSA). Magnetic resonance imaging (MRI) is the standard for quantifying tongue fat. Ultrasound echo intensity has been shown to correlate to fat content in skeletal muscles but has yet to be studied in the tongue. The objective of this study is to evaluate the relationship between ultrasound echo intensity and tongue fat. Methods Ultrasound coronal cross-sections of ex-vivo cow tongues were recorded at baseline and following three 1 milliliter serial injections of fat into the tongue. In humans, adults with and without OSA had submental ultrasound coronal cross-sections of their posterior tongue. Average echo intensity of the tongues (cow/human) were calculated in ImageJ software. Head and neck MRI were obtained on human subjects to quantify tongue fat volume. Echo intensity was compared to injected fat volume or MRI derived tongue fat percentage. Results Echo intensity in cow tongues showed a positive correlation to injected fat volume (rho = 0.93, p<0.001). In human subjects, echo intensity of the tongue base strongly correlated with MRI-calculated fat percentage for both the posterior tongue (rho = 0.95, p<0.001) and entire tongue (rho = 0.62, p<0.001). Larger tongue fat percentages (rho = 0.38, p=0.001) and higher echo intensity (rho = 0.27, p=0.024) were associated with more severe apnea-hypopnea index, adjusted for age, BMI, sex and race. Conclusions Ultrasound echo intensity is a viable surrogate measure for tongue fat volume and may provide a convenient modality to characterize tongue fat in OSA.

scholarly journals Myosoft: An automated muscle histology analysis tool using machine learning algorithm utilizing FIJI/ImageJ software

PLoS ONE ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. e0229041 ◽  
Author(s):  
Lucas Encarnacion-Rivera ◽  
Steven Foltz ◽  
H. Criss Hartzell ◽  
Hyojung Choo
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Analysis Tool ◽  
Machine Learning Algorithm ◽  
Muscle Histology ◽  
Imagej Software
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