Thierry Pécot

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PTEN (Phosphatase and tensin homolog deleted on chromosome 10) expression in stromal fibroblasts suppresses epithelial mammary tumours, but the underlying molecular mechanisms remain unknown. Using proteomic and expression profiling, we show that Pten loss from mammary stromal fibroblasts activates an oncogenic secretome that orchestrates the(More)
Green Fluorescent Protein (GFP)-tagging and time-lapse flu-orescence microscopy enable to observe molecular dynamics and interactions in live cells. Original image analysis methods are then required to process challenging 2D or 3D image sequences. To address the tracking problem of several hundreds of objects, we propose an original framework that provides(More)
The endocycle is a variant cell cycle consisting of successive DNA synthesis and gap phases that yield highly polyploid cells. Although essential for metazoan development, relatively little is known about its control or physiologic role in mammals. Using lineage-specific cre mice we identified two opposing arms of the E2F program, one driven by canonical(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(More)
GFP-tagging and time-lapse fluorescence microscopy can be considered as investigation tools to observe molecular dynamics and interactions in live cells at both the microscopic and nanoscopic scales. Consequently, it is imperative to develop novel image analysis techniques able to quantify dynamics of biological processes observed in such image sequences.(More)
This paper describes an original method to detect XFP-tagged proteins in time-lapse microscopy. Non-local measurements able to capture spatial intensity variations are incorporated within a Conditional Random Field (CRF) framework to localize the objects of interest. The minimization of the related energy is performed by a min-cut/max-flow algorithm.(More)
To develop better image change detection algorithms, new models able to capture spatio-temporal regularities and geometries present in an image pair are needed. In this paper, we propose a multiscale formulation for modeling semi-local inter-image interactions and detecting local or regional changes in an image pair. By introducing dissimilarity measures to(More)
To develop better image change detection algorithms, new models able to capture all the spatio-temporal regularities and geometries seen in an image pair are needed. In contrast to the usual pixel-wise methods, we propose a patch-based formulation for modeling semi-local interactions and detecting occlusions and other local or regional changes in an image(More)
Change detection between two images is challenging and needed in a wide variety of imaging applications. Several approaches have been yet developed, especially methods based on difference image. In this paper, we propose an original patch-based Markov modeling framework to detect spatial irregularities in the difference image with low false alarm rates.(More)