BoneJ2 - refactoring established research software

Domander, Richard; Felder, Alessandro; Doube, Michael

doi:10.12688/wellcomeopenres.16619.1

Cited by 87 publications

(28 citation statements)

References 13 publications

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“…We also report the effect of input parameters more in-depth (details in the electronic supplementary material, (a)). EF is available freely as part of the latest B one J, a collection of I mage J plug-ins intended for skeletal biology [ 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

The plate-to-rod transition in trabecular bone loss is elusive

et al. 2021

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Changes in trabecular micro-architecture are key to our understanding of osteoporosis. Previous work focusing on structure model index (SMI) measurements have concluded that disease progression entails a shift from plates to rods in trabecular bone, but SMI is heavily biased by bone volume fraction. As an alternative to SMI, we proposed the ellipsoid factor (EF) as a continuous measure of local trabecular shape between plate-like and rod-like extremes. We investigated the relationship between EF distributions, SMI and bone volume fraction of the trabecular geometry in a murine model of disuse osteoporosis as well as from human vertebrae of differing bone volume fraction. We observed a moderate shift in EF median (at later disease stages in mouse tibia) and EF mode (in the vertebral samples with low bone volume fraction) towards a more rod-like geometry, but not in EF maximum and minimum. These results support the notion that the plate to rod transition does not coincide with the onset of bone loss and is considerably more moderate, when it does occur, than SMI suggests. A variety of local shapes not straightforward to categorize as rod or plate exist in all our trabecular bone samples.

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Section: Introductionmentioning

confidence: 99%

The plate-to-rod transition in trabecular bone loss is elusive

et al. 2021

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“…To gauge the reproducibility of our segmentation, we additionally used 'intersection over union' [28] as a metric to quantify overlap between segmentations performed both before and after foramina-sealing. Intersection over union was calculated with a custom ImageJ [29,30] (https://doi.org/10.5281/zenodo.1427262) macro, available as part of https://zenodo.org/badge/ latestdoi/341621577.…”

Section: Methods For Addressing the Presence Of Intra-cortical Foramina And Porositymentioning

confidence: 99%

A new straightforward method for semi-automated segmentation of trabecular bone from cortical bone in diverse and challenging morphologies

et al. 2021

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Many physiological, biomechanical, evolutionary and clinical studies that explore skeletal structure and function require successful separation of trabecular from cortical compartments of a bone that has been imaged by X-ray micro-computed tomography (micro-CT) prior to analysis. Separation often involves manual subdivision of these two similarly radio-opaque compartments, which can be time-consuming and subjective. We have developed an objective, semi-automated protocol which reduces user bias and enables straightforward, user-friendly segmentation of trabecular from the cortical bone without requiring sophisticated programming expertise. This method can conveniently be used as a ‘recipe’ in commercial programmes (Avizo herein) and applied to a variety of datasets. Here, we characterize and share this recipe, and demonstrate its application to a range of murine and human bone types, including normal and osteoarthritic specimens, and bones with distinct embryonic origins and spanning a range of ages. We validate the method by testing inter-user bias during the scan preparation steps and confirm utility in the architecturally challenging analysis of growing murine epiphyses. We also report details of the recipe, so that other groups can readily re-create a similar method in open access programmes. Our aim is that this method will be adopted widely to create a reproducible and time-efficient method of segmenting trabecular and cortical bone.

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“…The current implementation has been developed in the Java programming language for the popular scientific image processing platform ImageJ [16]. The simplest and recommended way to install the software is by installing the Fiji Is Just ImageJ (Fiji) [17] bundle from , and adding the BoneJ update site [18] to Fiji according to the instructions at . This installs the command in the user menus, which can be found using the keyboard shortcut [L] or using the search bar in the ImageJ GUI.…”

Section: Installation and Code Availabilitymentioning

confidence: 99%

“…BoneJ source code and changes: . BoneJ release on Zenodo [31] doi:10.5281/zenodo.372642210.5281/zenodo.3726422. Test images and performance testing results doi:10.6084/m9.figshare.1186054210.6084/m9.figshare.11860542.…”

Section: Data Accessibilitymentioning

confidence: 99%

Multithreaded two-pass connected components labelling and particle analysis in ImageJ

Doube

2021

R. Soc. open sci.

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Sequential region labelling, also known as connected components labelling, is a standard image segmentation problem that joins contiguous foreground pixels into blobs. Despite its long development history and widespread use across diverse domains such as bone biology, materials science and geology, connected components labelling can still form a bottleneck in image processing pipelines. Here, I describe a multithreaded implementation of classical two-pass sequential region labelling and introduce an efficient collision resolution step, ‘ bucket fountain’ . Code was validated on test images and against commercial software (Avizo). It was performance tested on images from 2 MB (161 particles) to 6.5 GB (437 508 particles) to determine whether theoretical linear scaling ( O (n)) had been achieved, and on 1–40 CPU threads to measure speed improvements due to multithreading. The new implementation achieves linear scaling ( b = 0.905–1.052, time ∝ pixels b ; R 2 = 0.985–0.996), which improves with increasing thread number up to 8–16 threads, suggesting that it is memory bandwidth limited. This new implementation of sequential region labelling reduces the time required from hours to a few tens of seconds for images of several GB, and is limited only by hardware scale. It is available open source and free of charge in BoneJ.

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BoneJ2 - refactoring established research software

Cited by 87 publications

References 13 publications

The plate-to-rod transition in trabecular bone loss is elusive

The plate-to-rod transition in trabecular bone loss is elusive

A new straightforward method for semi-automated segmentation of trabecular bone from cortical bone in diverse and challenging morphologies

Multithreaded two-pass connected components labelling and particle analysis in ImageJ

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