C. Kervrann - Academia.edu (original) (raw)

Papers by C. Kervrann

The study of membrane plasticity and the role of molecular "machines" in the control of... more The study of membrane plasticity and the role of molecular "machines" in the control of biogenesis of the endo-cellular membranes have highlighted the crucial role of the "Rab" GTPases family as organizing centers of functional molecular platforms. Yet, to understand the regulation and coordination of these molecular assemblies, which are responsible for intracellular dynamic architectures, a more global vision, the development and the correlation of approaches at different spatial and temporal scales are needed. Considering the "fickle" nature of such dynamic architectures, the current performance of image acquisition systems and the analytical tools at our disposal, many technological challenges must be overcome. Dynamic aspects of perspectives described above require conceptual developments, particularly in the field of microscopy imaging. Moreover, to extract maximum information on the same sample, the development of an adapted microscopy, correlating different modalities, is needed. Last but not least, accurate image descriptors, allowing automatic detection and classification of molecular behavior in space and time, are indispensable. In this talk, we will focus on unsupervised change detection algorithms and new image modeling able to capture spatio-temporal regularities and geometries present in an image pair. In contrast to the usual pixel-wise methods and Markov Random Fields methods, we propose a patch-based formulation for modeling semi-local interactions and detecting local or regional changes in a microscopy image pair. By introducing dissimilarity measures to compare patches and binary local decisions, we design collaborative decision rules that use the total number of detections made by individual neighboring pixels, for different patch sizes. First, we will describe the patch-based representation for image pair analysis and present collaborative decision rules in neighborhoods. In addition, we will present the algorithm used to fuse binary decisions with statistical tests, at different spatial scales. Experimental results in video-microscopy (TIRF and wide-field imaging) demonstrate that the detection algorithm (with no optical flow computation) performs well at detecting meaningful changes and appearing/disappearing spots at the cell membrane. We also illustrate the approach for probabilistic local and global colocalization analysis of molecules in dual-color confocal images.

ABSTRACTIn theCaenorhabditis eleganszygote, astral microtubules generate forces, pushing against ... more ABSTRACTIn theCaenorhabditis eleganszygote, astral microtubules generate forces, pushing against and pulling from the cell periphery. They are essential to position the mitotic spindle. By measuring the dynamics of astral microtubules at the cortex, we revealed the presence of two populations, residing there for 0.4 s and 1.8 s, which correspond to the pulling and pushing events, respectively. Such an experiment offers a unique opportunity to monitor both forces that position the spindle under physiological conditions and study their variations along the anteroposterior axis (space) and the mitotic progression (time). By investigating pulling-force-generating events at the microscopic level, we showed that an anteroposterior asymmetry in dynein on-rate – encoding pulling-force imbalance – is sufficient to cause posterior spindle displacement. The regulation by spindle position – reflecting the number of microtubule contacts in the posterior-most region – reinforces this imbalance on...

3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano, 2006.

This paper presents a framework for tracking fluorescent objects imaged with 3D+time video-micros... more This paper presents a framework for tracking fluorescent objects imaged with 3D+time video-microscopy. The proposed technique solves the NP-hard problem of the multi-frame object correspondence. For this purpose, we use the simulated annealing algorithm for its flexibility for feature correspondence and its ability to give results in a very short time. Our approach takes into account events like "split", "merge", "birth" and "death". These "evolutionary events" are motivated by biological and physical considerations. We demonstrate the performance of the proposed algorithm on images of carcinoma NBT-II cells expressing fluorescent LAR-PTP, a tyrosine phosphatase possibly involved in tumor progression.

Nature Methods, 2014

workshop held as part of the study reported in this article. They also acknowledge their collabor... more workshop held as part of the study reported in this article. They also acknowledge their collaborators and financial support from their funding agencies. E.M.

Colocalizing two fluorescent-labeled proteins remains an open issue in diffraction-limited micro-... more Colocalizing two fluorescent-labeled proteins remains an open issue in diffraction-limited micro-scopy and raises new challenges with the emergence of super-resolution imaging, single molecule tagging (PALM, dSTORM...) and high content screening. Two distinct colocalization approaches are usually considered to address this problem : the intensity-based methods are very popular but are known to be sensitive to high intensity backgrounds and provide errors if the signal-to-noise ratio (SNR) is low ; the object-based methods analyze the spatial distribution of the two sets of detected spots by using point process statistics but unfortunately get rid of valuable information by reducing objects to points. We propose a unique method (GcoPS : Geo-coPositioning System) that reconciles intensity-based and object-based methods for various applications in both conventional diffraction-limited and super-resolution microscopy. Unlike previous methods, GcoPS is very fast, robust-to-noise and vers...

Open science and FAIR principles have become major topics in the field of bioimaging. This is due... more Open science and FAIR principles have become major topics in the field of bioimaging. This is due to both new data acquisition technologies that generate large datasets, and new analysis approaches that automate data mining with high accuracy. Nevertheless, data are rarely shared and rigorously annotated because it requires a lot of manual and tedious management tasks and software packaging. We present BioImageIT, an open-source framework for integrating data management according to FAIR principles with data processing.

While fluorescent microscopy imaging has become the spearhead of modern biology as it is able to ... more While fluorescent microscopy imaging has become the spearhead of modern biology as it is able to generate long-term videos depicting 4D nanoscale cell behaviors, it is still limited by the optical aberrations and the photon budget available in the specimen and to some extend to photo-toxicity. A direct consequence is the necessity to develop flexible and “off-road” algorithms in order to recover structural details and improve spatial resolution, which is critical when pushing the illumination to the low levels in order to limit photo-damages. Moreover, as the processing of very large temporal series of images considerably slows down the analysis, special attention must be paid to the feasibility and scalability of the developed restoration algorithms. To address these specifications, we present a very flexible method designed to restore 2D-3D+Time fluorescent images and subtract undesirable out-of-focus background. We assume that the images are sparse and piece-wise smooth, and are ...

Patch-Based Techniques in Medical Imaging, 2018

We propose a statistical method to address an important issue in cryo electron tomography image a... more We propose a statistical method to address an important issue in cryo electron tomography image analysis: reduction of a high amount of noise and artifacts due to the presence of a missing wedge (MW) in the spectral domain. The method takes as an input a 3D tomogram derived from limited-angle tomography, and gives as an output a 3D denoised and artifact compensated tomogram. The artifact compensation is achieved by filling up the MW with meaningful information. The method can be used to enhance visualization or as a pre-processing step for image analysis, including segmentation and classification. Results are presented for both synthetic and experimental data.

Background and ObjectivesCryo electron tomography visualizes native cells at nanometer resolution... more Background and ObjectivesCryo electron tomography visualizes native cells at nanometer resolution, but analysis is challenged by noise and artifacts. Recently, supervised deep learning methods have been applied to decipher the 3D spatial distribution of macromolecules. However, in order to discover unknown objects, unsupervised classification techniques are necessary. In this paper, we provide an overview of unsupervised deep learning techniques, discuss the challenges to analyze cryo-ET data, and provide a proof-of-concept on real data.MethodsWe propose an unsupervised sub-tomogram classification method based on transfer learning. We use a deep neural network to learn a clustering friendly representation able to capture 3D shapes in the presence of noise and artifacts. This representation is learned here from a synthetic data set.ResultsWe show that when applying k-means clustering given a learning-based representation, it becomes possible to satisfyingly classify real sub-tomogram...

(C) Overview of cluster of metaphase chromosomes from a Drosophila embryo visualized using fluore... more (C) Overview of cluster of metaphase chromosomes from a Drosophila embryo visualized using fluorescence microscopy showing the DAPI (blue) and histone (green) fluorescence. (A) PALM image of region in lower box in (A). Red arrowheads point to filamentous structures. See Fig 3 in: A Matsuda et al. (2010) Condensed mitotic chromosme structure at nanometer resolution using PALM and EGFP-histones. PLOSone 5:e12768.

Cryo-electron tomography (cryo-ET) visualizes the 3D spatial distribution of macromolecules at na... more Cryo-electron tomography (cryo-ET) visualizes the 3D spatial distribution of macromolecules at nanometer resolution inside native cells. While this label-free cryogenic imaging technology produces data containing rich structural information, automated identification of macromolecules inside cellular tomograms is challenged by noise and reconstruction artifacts, as well as the presence of many molecular species in the crowded volumes. Here, we present a computational procedure that uses artificial neural networks to simultaneously localize with a multi-class strategy several macromolecular species in cellular cryo-electron tomograms. Once trained, the inference stage of DeepFinder is significantly faster than template matching, and performs better than other competitive deep learning methods at identifying macromolecules of various sizes in both synthetic and experimental datasets. On cellular cryo-ET data, DeepFinder localized membrane-bound and cytosolic ribosomes (~3.2 MDa), Rubis...

2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 2015

Assessing the dynamics of plasma membrane diffusion processes in live cell fluorescence microscop... more Assessing the dynamics of plasma membrane diffusion processes in live cell fluorescence microscopy is of paramount interest to understand cell mechanisms. We propose a new method to detect vesicle fusion events, and estimate the associated diffusion coefficients in image sequences of total internal reflection fluorescence microscopy (TIRFM). In contrast to usual approaches, a diffusion coefficient is locally estimated for each detected fusing vesicle. We first detect the membrane fusion events and then select the diffusion configurations among them with a correlation test. To estimate the diffusion coefficient, a geometric model is fitted to the detected spot directly in the 2D+t subvolume. Quantitative results demonstrate the accuracy of the proposed method.

2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010

Endocytosis/recycling and exocytosis are mechanisms conserved through evolution allowing cells to... more Endocytosis/recycling and exocytosis are mechanisms conserved through evolution allowing cells to communicate with their external medium. In order to study these dynamic processes, the present work proposes a patch-based method for detecting recycling or exocytotic events at the Plasma membrane in fast TIRF microscopy combined with the computation of normalized temporal representations of those events. Evaluation, performed on TIRF sequences showing Transferrin receptor (TfR) recycling, validates a high detection rate fully compatible with an automatic data extraction and analysis of the plasma membrane recycling process.

Proceedings of the Seventh IEEE International Conference on Computer Vision, 1999

An energy model-based approach for estimating object boundaries is presented. We study a particul... more An energy model-based approach for estimating object boundaries is presented. We study a particular energy, which minimizer can be determined. The method estimates the unknown number of objects and draws object boundaries by selecting the "best" level lines computed from level sets of the original image. Unlike previous standard methods, the proposed method does not require iteration for minimizing the energy. In addition, our segmentation algorithm combines anisotropic diffusion-based regularization with level line selection to extract smooth object boundaries. Experimental results on 2D biomedical and meteorological images are reported.

Image sequence analysis in video-microscopy for life sciences now has gained importance since mol... more Image sequence analysis in video-microscopy for life sciences now has gained importance since molecular biology is presently having a profound impact on the way research is being conducted in medicine. However, the image processing techniques that are currently used for modeling intracellular dynamics are still relatively crude. Indeed, complex interactions between a large number of small moving particles in a complex scene cannot be easily modeled, which limits the performance of object detection and tacking algorithms. This motivates our present research effort which is to develop a general estimation/simulation framework able to produce image sequences showing small moving spots in interaction and with variable velocities, corresponding to intracellular dynamics and trafficking in biology. It is now well established that spot trajectories can play a role in analysis of living cell dynamics and simulate realistic image sequences is then of major importance. We demonstrate the potential of the proposed simulation/estimation framework in experiments, and show that this approach can be also used to evaluate the performance of object detection/tracking algorithms in video-microscopy.

Lecture Notes in Computer Science

The study of protein dynamics is essential for understanding the multi-molecular complexes at sub... more The study of protein dynamics is essential for understanding the multi-molecular complexes at subcellular levels. Fluorescent Protein (XFP)-tagging and time-lapse fluorescence microscopy enable to observe molecular dynamics and interactions in live cells, unraveling the live states of the matter. Original image analysis methods are then required to process challenging 2D or 3D image sequences. Recently, tracking methods that estimate the whole trajectories of moving objects have been successfully developed. In this paper, we address rather the detection of meaningful events in spatio-temporal fluorescence image sequences, such as apparent stable "stocking areas" involved in membrane transport. We propose an original patch-based Markov modeling to detect spatial irregularities in fluorescence images with low false alarm rates. This approach has been developed for real image sequences of cells expressing XFP-tagged Rab proteins, known to regulate membrane trafficking.

Proceedings of the National Academy of Sciences, 2012

In vivo, F-actin flows are observed at different cell life stages and participate in various deve... more In vivo, F-actin flows are observed at different cell life stages and participate in various developmental processes during asymmetric divisions in vertebrate oocytes, cell migration, or wound healing. Here, we show that confinement has a dramatic effect on F-actin spatiotemporal organization. We reconstitute in vitro the spontaneous generation of F-actin flow using Xenopus meiotic extracts artificially confined within a geometry mimicking the cell boundary. Perturbations of actin polymerization kinetics or F-actin nucleation sites strongly modify the network flow dynamics. A combination of quantitative image analysis and biochemical perturbations shows that both spatial localization of F-actin nucleators and actin turnover play a decisive role in generating flow. Interestingly, our in vitro assay recapitulates several symmetry-breaking processes observed in oocytes and early embryonic cells.

IEEE Transactions on Image Processing, 2009

In image processing, restoration is expected to improve the qualitative inspection of the image a... more In image processing, restoration is expected to improve the qualitative inspection of the image and the performance of quantitative image analysis techniques. In this paper, an adaptation of the Non Local (NL-) means filter is proposed for speckle reduction in ultrasound (US) images. Originally developed for additive white Gaussian noise, we propose to use a Bayesian framework to derive a NL-means filter adapted to a relevant ultrasound noise model. Quantitative results on synthetic data show the performances of the proposed method compared to well-established and state-of-the-art methods. Results on real images demonstrate that the proposed method is able to preserve accurately edges and structural details of the image.