Automated heart rate estimation in fish embryo

International audienceTransparent organisms such as fish embryos are being increasingly used for environmental toxicology studies. These studies require estimating a number of physiological parameters. These estimations may be diverse in nature and can be a challenge to automate. Among these, an example is the development of reliable and repeatable automated assays for the determination of heart rates. To achieve this, most existing method rely on cyclical luminance variations, since as the heart fills and empties, it become respectively brighter and darker. However, sometimes direct measurement of the heart rate may be difficult, depending on the age of the embryo, its actual transparency, and its aspect under the microscope. It may be easier to seek an indirect measurement. In this article, we estimate the heart function parameters, such as heart frequency, either from measuring the heart motion or from blood flow in arteries. This measurement is more complex from the image analysis point of view, but it is more precise, more physically meaningful and easier to use in practice and to automate than measuring illumination changes. It may also be more informative. We illustrate on medaka embryos

Automatic detection of beating cilia with frequencies estimations

International audienceMuco-ciliary clearance is the airway first mechanism of defence against environmental attacks such as microorganisms or pollution. Cilia motility impairment can be either of genetic (primary ciliary dyskinesia) or acquired origin (environmental attacks), entailing chronic diseases. It is of interest for practitioners to evaluate cilia beating frequency easily, robustly and reliably. As yet, no fully automatized method is available. 2 Methods Ciliated cells were sampled in patients by brushing nasal mucosa and cilia beating was recorded using high speed video microscopy. We first estimated and removed the sensor pattern. We then stabilized the sequence assuming rigid transforms. We retained only the moving parts of the sequence and, after deblurring, characterized and segmented the moving parts in several regions of interest. The frequency was estimated for each region

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

International audienceAs image processing and analysis techniques improve, an increasing number of procedures in bio-medical analyses can be automated. This brings many benefits, e.g improved speed and accuracy, leading to more reliable diagnoses and follow-up, ultimately improving patients outcome. Many automated procedures in bio-medical imaging are well established and typically consist of detecting and counting various types of cells (e.g. blood cells, abnormal cells in Pap smears, and so on). In this article we propose to automate a different and difficult set of measurements, which is conducted on the cilia of people suffering from a variety of respiratory tract diseases. Cilia are slender, microscopic, hair-like structures or organelles that extend from the surface of nearly all mammalian cells. Motile cilia, such as those found in the lungs and respiratory tract, present a periodic beating motion that keep the airways clear of mucus and dirt. In this paper, we propose a fully automated method that computes various measurements regarding the motion of cilia, taken with high-speed video-microscopy. The advantage of our approach is its capacity to automatically compute robust, adaptive and regionalized measurements, i.e. associated with different regions in the image. We validate the robustness of our approach, and illustrate its performance in comparison to the state-of-the-art

Analyse du mouvement pour applications médicales et bio-médicales

Motion analysis, or the analysis of image sequences, is a natural extension of image analysis to time series of images. Many methods for motion analysis have been developed in the context of computer vision, including feature tracking, optical flow, keypoint analysis, image registration, and so on. In this work, we propose a toolbox of motion analysis techniques suitable for biomedical image sequence analysis. We particularly study ciliated cells. These cells are covered with beating cilia. They are present in humans in areas where fluid motion is necessary. In the lungs and the upper respiratory tract, Cilia perform the clearance task, which means cleaning the lungs of dust and other airborne contaminants. Ciliated cells are subject to genetic or acquired diseases that can compromise clearance, and in turn cause problems in their hosts. These diseases can be characterized by studying the motion of cilia under a microscope and at high temporal resolution. We propose a number of novel tools and techniques to perform such analyses automatically and with high precision, both ex-vivo on biopsies, and in-vivo. We also illustrate our techniques in the context of eco-toxicity by analysing the beating pattern of the heart of fish embryoL’analyse du mouvement, ou l’analyse d’une séquence d’images, est l’extension naturelle de l’analyse d’images à l’analyse de séries temporelles d’images. De nombreuses méthodes d’analyse de mouvement ont été développées dans le contexte de la vision par ordinateur, incluant le suivi de caractéristiques, le flot optique, l’analyse de points-clef, le recalage d’image, etc. Dans ce manuscrit, nous proposons une boite a outils de techniques d’analyse de mouvement adaptées à l’analyse de séquences biomédicales. Nous avons en particulier travaillé sur les cellules ciliées qui sont couvertes de cils qui battent. Elles sont présentes chez l’homme dans les zones nécessitant des mouvements de fluide. Dans les poumons et les voies respiratoires supérieures, les cils sont responsables de l’épuration muco-ciliaire, qui permet d’évacuer des poumons la poussière et autres impuretés inhalées. Les altérations de l’épuration mucociliaire peuvent être liées à des maladies touchant les cils, pouvant être génétiques ou acquises et peuvent être handicapantes. Ces maladies peuvent être caractérisées par l’analyse du mouvement des cils sous un microscope avec une résolution temporelle importante. Nous avons développé plusieurs outils et techniques pour réaliser ces analyses de manière automatiques et avec une haute précision, à la fois sur des biopsies et in-vivo. Nous avons aussi illustré nos techniques dans le contexte d’éco-toxicité en analysant le rythme cardiaque d’embryons de poisson

Morphologie Mathématique et traitement d'images

International audienceDans ce chapitre nous présentons la Morphologie Mathématique comme une approche non linéaire du traitement d'images, basée sur des critères de forme et de taille. Nous essaierons de montrer son attrait en mettant en avant l'élégance de sa théorie ainsi que la puissance des outils qu'elle permet de construire : fonction distance, filtres, algorithme du Watershed pour la segmentation et autres représentations hiérarchiques, pour les principaux

Periodic Area-of-Motion characterization for Bio-Medical applications

International audienceMany 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

An Automated Assay for the Evaluation of Mortality in Fish Embryo

International audienceWaterways are often first and severely affected by pollution. In this context, fish embryos – which constitute a good model for sensitivity to chemicals – are widely used in environmental toxicology studies. Such studies are devoted to the analysis of a wide spectrum of physiological parameters, for instance mortality ratio. In this article, we develop an assay to determine the mortality rate of Medaka embryo. Based on video sequences, our purpose is to obtain reliable, repeatable results in a fully automated fashion. To reach that challenging goal, we develop an efficient morphological pipeline that analyses image sequences in a multiscale paradigm, from the global scene to the embryo, and then to its heart, finally analysing its putative motion, characterized by intensity variations. Our pipeline, based on robust morphological operators, has a low computational cost, and was experimentally assessed on a dataset consisting of 660 images, providing a success ratio higher than 99%

Going beyond p-Convolutions to Learn Grayscale Morphological Operators

International audienceIntegrating mathematical morphology operations within deep neural networks has been subject to increasing attention lately. However, replacing standard convolution layers with erosions or dilations is particularly challenging because the min and max operations are not differentiable. Relying on the asymptotic behavior of the counter-harmonic mean, p-convolutional layers were proposed as a possible workaround to this issue since they can perform pseudo-dilation or pseudo-erosion operations (depending on the value of their inner parameter p), and very promising results were reported. In this work, we present two new morphological layers based on the same principle as the p-convolutional layer while circumventing its principal drawbacks, and demonstrate their potential interest in further implementations within deep convolutional neural network architectures

An automated assay for the assessment of cardiac arrest in fish embryo

International audienceStudies on fish embryo models are widely developed in research. They are used in several research field such as drug discovery or environmental toxicology. In this article, we propose an entirely automated assay to detect cardiac arrest in Medaka (Oryzias latipes) based on image analysis. We propose a multi-scale pipeline based on mathematical morphology. Starting from video sequences of entire wells in 24-well plates, we focus on the embryo, detect its heart, and ascertain whether or not the heart is beating based on intensity variation analysis. Our image analysis pipeline only uses commonly available operators. It has a low computational cost, allowing analysis at the same rate as acquisition. From an initial dataset of 3,192 videos, 660 were discarded as unusable (20.7%), 655 of them correctly so (99.25%) and only 5 incorrectly so (0.75%). The 2,532 remaining videos were used for our test. On these, 45 errors were made, leading to a success rate of 98.23%