Automating the measurement of physiological parameters: A case study in the image analysis of cilia motion

Puybareau, Élodie; Talbot, Hugues; Béquignon, E.; Louis, Bruno; Pelle, Gabriel; Papon, Jean‐François; Coste, A.; Najman, Laurent

doi:10.1109/icip.2016.7532556

Cited by 5 publications

(5 citation statements)

References 15 publications

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“…This feature allows Cilialyzer to remove the undesirable sample motion through the use of its Python package 'pyStackReg' [26], which results in the alignment of consecutive images in the sequence to remain in place. The other notable pre-processing method offered by Cilialyzer is the "motion extraction" feature, which is performed via a computational function termed "mean image subtraction" previously described in the literature [27], [28]. Motion extraction removes the static background of an image, which was demonstrated to enhance the visualization of the cilia along with their movement in the selected ROI.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of Open-Source Ciliary Analysis Software in Primary Ciliary Dyskinesia: A Comparative Assessment

Demetriou,

Muñiz-Hernández,

Rosario-Ortiz

et al. 2024

Preprint

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Primary Ciliary Dyskinesia (PCD) is a rare genetic disorder characterized by alterations in motile cilia func-tion. The diagnosis of PCD is challenging due to the lack of standardized methods in clinical practice. High-speed video microscopy analysis (HSVA) directly evaluates ciliary beat frequency (CBF) in PCD. Recently, open-source ciliary analysis software applications have shown promise in measuring CBF accurately. How-ever, there is limited knowledge about the performance of different software applications, creating a gap in understanding their comparative effectiveness in measuring CBF in PCD. We compared two open-source software applications, CiliarMove and Cilialyzer, against the manual count method. We used videos rec-orded at high-speed of nasal ciliary brush samples from PCD patients and healthy controls. All three meth-ods showed lower median CBF values in PCD patients than healthy controls. CiliarMove and Cilialyzer identified lower CBF in PCD patients, similar to the manual count. Cilialyzer, CiliarMove and manual count demonstrated statistical significance (p-value < 0.0001) in the difference of median CBF values be-tween PCD and healthy controls. These findings support the utility of open-source software-based analysis tools. Further studies are needed to validate these findings with other genetic variants and identify the op-timal software for accurate CBF measurement in PCD.

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Section: Discussionmentioning

confidence: 99%

Evaluation of Open-Source Ciliary Analysis Software in Primary Ciliary Dyskinesia: A Comparative Assessment

Demetriou,

Muñiz-Hernández,

Rosario-Ortiz

et al. 2024

Preprint

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“…As has been shown previously (e.g. see [6, 7]), the high-speed recordings need to be adequately preprocessed before getting analyzed. In the following, we describe the available video-preprocessing steps, which mainly take care of the removal of disturbing movements and vibrations of the whole sample and the removal of the static background, emphasizing the actual signal of interest.…”

Section: Methodsmentioning

confidence: 99%

“…As has been shown e.g. in [6, 7], the static background of an image sequence I[ x, y, t ] can be removed by subtracting the mean image: …”

Section: Methodsmentioning

confidence: 99%

“…In the rst line of research, dedicated computational methods aiming at the quantitative, objective and automated detection of defects in the ciliary motion on detached and immersed respiratory epithelial cells are developed [6][7][8][9][10][11][12][13][14][15]. ose studies mainly focus on the quantitative and automated characterization of the ciliary motion pa ern of individual cilia and therefore, at making the conventional HSVM approach observer-independent.…”

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confidence: 99%

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The Cilialyzer – a freely available open-source software for a standardised identification of impaired mucociliary activity facilitating the diagnostic testing for PCD

Schneiter

Tschanz

Müller

et al. 2022

Preprint

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Background and Objective: Primary ciliary dyskinesia (PCD) is a rare genetic disorder causing a defective ciliary structure, which predominantly leads to an impaired mucociliary clearance and associated airway disease. As there is currently no single diagnostic gold standard test, PCD is diagnosed by a combination of several methods comprising genetic testing and the examination of the ciliary structure and function. Among the approved diagnostic methods, only high-speed video microscopy (HSVM) allows to directly observe the ciliary motion and therefore, to directly assess ciliary function. In the present work, we present our recently developed freely available open-source software - termed 'Cilialyzer, which has been specifically designed to support and facilitate the analysis of the mucociliary activity in respiratory epithelial cells captured by high- speed video microscopy. Methods: In its current state, the Cilialyzer software enables clinical PCD diagnosticians to load, preprocess and replay the image sequences with a feature-rich replaying module facilitating the commonly performed qualitative visual assessment of ciliary function. The image processing methods made accessible through an intuitive user interface allow clinical specialists to comfortably compute the ciliary beating frequency (CBF), the activity map and the 'frequency correlation length' - an observable getting newly introduced. Furthermore, the Cilialyzer contains a simple-to-use particle tracking interface to determine the mucociliary transport speed. Results: The Cilialyzer is fully written in the Python programming language and freely available under the terms of the MIT license. The proper functioning of the computational analysis methods constituting the Cilialyzer software is demonstrated by using simulated and representative sample data from clinical practice. Conclusions: The Cilialyzer serves as a useful clinical tool for standardised PCD diagnostics and provides new quantitative information awaiting to be clinically evaluated using cohorts of PCD. As the Cilialyzer is freely available under the terms of a permissive open-source license, it serves as a ground frame for further development of computational methods aiming at the quantification and automation of the analysis of mucociliary activity captured by HSVM.

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“…In [5], unsupervised spectral clustering is used to detect these areas over a few frames. In previous work [6,7], we have used variance analysis on temporal gradient to propose area-of-motion identification. In [8], we used optical flow [9] for area of motion clustering.…”

Section: Introductionmentioning

confidence: 99%

Periodic area-of-motion characterization for bio-medical applications

Puybareau¹,

Talbot²,

Najman³

2017

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)

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Many bio-medical applications involve the analysis of sequences for motion characterization. In this article, we consider 2D+t sequences where a particular motion (e.g. a blood flow) is associated with a specific area of the 2D image (e.g. an artery) but multiple motions may exist simultaneously in the same sequences (e.g. there may be several blood vessels present, each with their specific flow). The characterization of this type of motion typically involves first finding the areas where motion is present, followed by an analysis of these motions: speed, regularity, frequency, etc. In this article, we propose a methodology called "area-of-motion characterization" suitable for simultaneously detecting and characterizing areas where motion is present in a sequence. We can then classify this motion into consistent areas using unsupervised learning and produce directly usable metrics for various applications. We illustrate this methodology for the analysis of cilia motion on ex-vivo human samples, and we apply and validate the same methodology for blood flow analysis in fish embryo.

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Automating the measurement of physiological parameters: A case study in the image analysis of cilia motion

Cited by 5 publications

References 15 publications

Evaluation of Open-Source Ciliary Analysis Software in Primary Ciliary Dyskinesia: A Comparative Assessment

Evaluation of Open-Source Ciliary Analysis Software in Primary Ciliary Dyskinesia: A Comparative Assessment

The Cilialyzer – a freely available open-source software for a standardised identification of impaired mucociliary activity facilitating the diagnostic testing for PCD

Periodic area-of-motion characterization for bio-medical applications

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