Dataset Information

Training to Improve Precision and Accuracy in the Measurement of Fiber Morphology.

ABSTRACT: An estimated $7.1 billion dollars a year is spent due to irreproducibility in pre-clinical data from errors in data analysis and reporting. Therefore, developing tools to improve measurement comparability is paramount. Recently, an open source tool, DiameterJ, has been deployed for the automated analysis of scanning electron micrographs of fibrous scaffolds designed for tissue engineering applications. DiameterJ performs hundreds to thousands of scaffold fiber diameter measurements from a single micrograph within a few seconds, along with a variety of other scaffold morphological features, which enables a more rigorous and thorough assessment of scaffold properties. Herein, an online, publicly available training module is introduced for educating DiameterJ users on how to effectively analyze scanning electron micrographs of fibers and the large volume of data that a DiameterJ analysis yields. The end goal of this training was to improve user data analysis and reporting to enhance reproducibility of analysis of nanofiber scaffolds. User performance was assessed before and after training to evaluate the effectiveness of the training modules. Users were asked to use DiameterJ to analyze reference micrographs of fibers that had known diameters. The results showed that training improved the accuracy and precision of measurements of fiber diameter in scanning electron micrographs. Training also improved the precision of measurements of pore area, porosity, intersection density, and characteristic fiber length between fiber intersections. These results demonstrate that the DiameterJ training module improves precision and accuracy in fiber morphology measurements, which will lead to enhanced data comparability.

SUBMITTER: Hotaling NA

PROVIDER: S-EPMC5132175 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Training to Improve Precision and Accuracy in the Measurement of Fiber Morphology.

Hotaling Nathan A NA Jeon Jun J Wade Mary Beth MB Luong Derek D Palmer Xavier-Lewis XL Bharti Kapil K Simon Carl G CG

PloS one 20161201 12

An estimated $7.1 billion dollars a year is spent due to irreproducibility in pre-clinical data from errors in data analysis and reporting. Therefore, developing tools to improve measurement comparability is paramount. Recently, an open source tool, DiameterJ, has been deployed for the automated analysis of scanning electron micrographs of fibrous scaffolds designed for tissue engineering applications. DiameterJ performs hundreds to thousands of scaffold fiber diameter measurements from a single ...[more]

PMID: 27907145

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Project description:IntroductionWound surface area measurement is important as therapeutic decisions may depend on the change of wound surface area over time. Digital planimetry is a popular technique in wound area measurement. It is accurate and repeatable when calibration is performed with 2 rulers placed at opposite sides of a wound. The aim of the current study was improving accuracy and precision of wound area measurement using capabilities of smart devices.MethodsThe correction of area measurement based on calculated camera tilt angle and the calculation of calibration coefficient of linear dimensions as weighted average were proposed. These and other improvements were applied in the Planimator app for Android, which was then used in the study. Accuracy and precision of the Planimator app were compared to the Visitrak device, the SilhouetteMobile device, the AreaMe software, and to the digital planimetry based on 2-ruler calibration with pictures taken by the smartphone, compact, and D-SLR cameras. Areas of 40 wound shapes of area ranged from 0.14 to 31.72 cm2 were measured with each device. Medians of relative errors (REs) were compared in the accuracy tests and standard deviations (SDs) of relative differences (RDs) were compared in the tests of precision.ResultsThe median of REs for the Planimator app was not significantly different from the medians of REs for the digital planimetry based on pictures from the compact or D-SLR cameras, but it was significantly lower than the medians of REs for the Visitrak and SilhouetteMobile devices, the AreaMe software and the digital planimetry based on pictures from a smartphone camera. The SD of RDs for the Planimator app was not significantly different from the SDs of RDs for the digital planimetry based on pictures from the compact or D-SLR cameras, but it was significantly lower than the SDs of RDs for the Visitrak and SilhouetteMobile devices, the AreaMe software and the digital planimetry based on pictures from a smartphone camera. The Planimator app installed at a smartphone revealed to be 2-fold more accurate and 1.5-fold more precise than the measurements with using ImageJ software based on pictures taken with the same smartphone.ConclusionsThe Planimator app occurred to have the same accuracy and precision as measurements with digital planimetry with 2-ruler calibration and based on pictures from a compact camera or a D-SLR camera. This app showed better accuracy and precision than the Visitrak and SilhouetteMobile devices, the AreaMe software and the digital planimetry based on pictures from a smartphone camera.

Dataset Information

Training to Improve Precision and Accuracy in the Measurement of Fiber Morphology.

Publications

Training to Improve Precision and Accuracy in the Measurement of Fiber Morphology.

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