Dataset Information

Automated Measurement of Blood Vessels in Tissues from Microscopy Images.

ABSTRACT: The quantification of tunica media thickness in histological cross sections is a ubiquitous exercise in cardiopulmonary research, yet the methods for quantifying medial wall thickness have never been rigorously examined with modern image analysis tools. As a result, inaccurate and cumbersome manual measurements of discrete wall regions along the vessel periphery have become common practice for wall thickness quantification. The aim of this study is to introduce, validate, and facilitate the use of an improved method for medial wall thickness quantification. We describe a novel method of wall thickness calculation based on image skeletonization and compare its results to those of common techniques. Using both theoretical and empirical approaches, we demonstrate the accuracy and superiority of the skeleton-based method for measuring wall thickness while discussing its interpretation and limitations. Finally, we present a new freely available software tool, the VMI Calculator, to facilitate wall thickness measurements using our novel method. © 2016 by John Wiley & Sons, Inc.

SUBMITTER: Kelly NJ

PROVIDER: S-EPMC6431235 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Automated Measurement of Blood Vessels in Tissues from Microscopy Images.

Kelly Neil J NJ Dandachi Nadine N Goncharov Dmitry A DA Pena Andressa Z AZ Radder Josiah E JE Gregory Alyssa D AD Lai Yen-Chun YC Leme Adriana S AS Gladwin Mark T MT Goncharova Elena A EA St Croix Claudette M CM Shapiro Steven D SD

Current protocols in cytometry 20161010

The quantification of tunica media thickness in histological cross sections is a ubiquitous exercise in cardiopulmonary research, yet the methods for quantifying medial wall thickness have never been rigorously examined with modern image analysis tools. As a result, inaccurate and cumbersome manual measurements of discrete wall regions along the vessel periphery have become common practice for wall thickness quantification. The aim of this study is to introduce, validate, and facilitate the use ...[more]

PMID: 27723088

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Project description:Objectives: Endometrial peristalsis (EP) in non-pregnant uterine can be assessed by visual assessment of transvaginal ultrasound (TVUS). However, visual assessment is subjective, and the outcome depends on the sonographers and video analysts. This study aimed to create a newly developed automatic analysis algorithm for measuring the EP compared to visual assessment. Methods: A retrospective analysis was performed using the datasets from in vitro fertilization and embryo transfer (IVF-ET), who underwent the evaluation of EP by TVUS within 5 days prior to transplantation. 158 cine TVUS images were used to develop the automated analysis algorithm, and 37 cine TVUS images were evaluated by both visual and automated analysis algorithms. The algorithm was developed by applying the optical flow technology and enabled objective analysis of the number, direction, and intensity of EP. Results: The number of peristaltic waves counted by visual assessment was 4.2 ± 2.3 (mean ± standard deviation) and 4.1 ± 2.1 for doctors one and two, respectively. The number of waves counted with the algorithm was 3.6 ± 2.1 at first evaluation and 3.7 ± 2.0 at repeated evaluation. A significant difference was found between the algorithm count and visual assessment (p = 0.001, 0.002, 0.003, 0.008). The ICC values for algorithm versus manuals ranged from 0.84 to 0.96 and 0.87 to 0.96. The numbers of the cervix-to-fundus (CF), fundus-to-cervix (FC), and both cervix-to-fundal and fundus-to-cervix (CF + FC) directions of EP counted by the algorithm were 50, 52, and 32, respectively. The numbers counted by visual assessment were 43, 45, and 46, respectively. The number of EP was the same in 87% of the two algorithm counts. The number was lower between the algorithm and visual analysis (79% with complete agreement). The EP intensity assessed by the algorithm was 2.6 ± 1.1, and the peristalsis velocity was 0.147 (0.07) mm/s. Conclusion: The fully automated analysis algorithm can be used to quantify uterine peristalsis comparable to visual assessment.

Dataset Information

Automated Measurement of Blood Vessels in Tissues from Microscopy Images.

Publications

Automated Measurement of Blood Vessels in Tissues from Microscopy Images.

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