A Theory for Multiresolution Signal Decomposition: The Wavelet Representation

It is now well admitted in the computer vision literature that a multi-resolution decomposition provides a useful image representation for vision algorithms. In this paper we show that the wavelet theory recently developed by the mathematician Y. Meyer enables us to understand and model the concepts of resolution and scale. In computer vision we generally do not want to analyze the images at each resolution level because the information is redundant. After processing the signal at a resolution r0, it is more efficient to analyze only the additional details which are available at a higher resolution rl. We prove that this difference of information can be computed by decomposing the signal on a wavelet orthonormal basis and that it can be efficiently calculated with a pyramid transform. This can also be interpreted as a division of the signal in a set of orientation selective frequency channels. Such a decomposition is particularly well adapted for computer vision applications such as signal coding, texture discrimination, edge detection, matching algorithms and fractal analysis

Dyadic Wavelets Energy Zero-Crossings

An important problem in signal analysis is to define a general purpose signal representation which is well adapted for developing pattern recognition algorithms. In this paper we will show that such a representation can be defined from the position of the zero-crossings and the local energy values of a dyadic wavelet decomposition. This representation is experimentally complete and admits a simple distance for pattern matching applications. It provides a multiscale decomposition of the signal and at each scale characterizes the locations of abrupt changes in the signal. We have developed a stereo matching algorithm to illustrate the application of this representation to pattern matching

Image Wavelet Decomposition and Applications

The general problem of computer vision has been investigated for more than twenty years and is still one of the most challenging fields in artificial intelligence. Indeed taking a look at the human visual system can give us an idea of the complexity of any solution to the problem of visual recognition. This general task can be decomposed into a whole hierarchy of problems ranging from pixel processing to high level segmentation and complex objects recognition. Contrasting an image at different representations provides useful information such as edges. First, we introduce an example of low level signal and image processing using the theory of wavelets which provides the basis for multiresolution representation. Like the human brain, we use a multiorientation process which detects features independently in different orientation sectors. So, we end up contrasting images of the same orientation but of different resolutions to gather information about an image. We then develop an interesting image representation using energy zero crossings. We show that this representation is experimentally complete and leads to some higher level applications such as edge and corner finding, which in turn provides two basic steps to image segmentation. We also discuss the possibilities of feedback between different levels of processing

Deep Network Classification by Scattering and Homotopy Dictionary Learning

International audienceWe introduce a sparse scattering deep convolutional neural network, which provides a simple model to analyze properties of deep representation learning for classification. Learning a single dictionary matrix with a classifier yields a higher classification accuracy than AlexNet over the ImageNet 2012 dataset. The network first applies a scattering transform that linearizes variabilities due to geometric transformations such as translations and small deformations. A sparse l1 dictionary coding reduces intra-class variability while preserving class separation through projections over unions of linear spaces. It is implemented in a deep convolutional network with a homotopy algorithm having an exponential convergence. A convergence proof is given in a general framework that includes ALISTA. Classification results are analyzed on ImageNet

MiR-21 Deficiency Alters the Survival of Ly-6Clo Monocytes in ApoE -/- Mice and Reduces Early-Stage Atherosclerosis.

Objective- To determine the role of miR-21 on the homeostasis of monocyte subsets and on atherosclerosis development in ApoE -/- mice. Approach and Results- In ApoE -/- mice, miR-21 expression was increased in circulating Ly-6Clo nonclassical monocytes in comparison to Ly-6Chi monocytes. The absence of miR-21 significantly altered the survival and number of circulating Ly-6Clo nonclassical monocytes in ApoE -/- mice. In the early stages of atherosclerosis, the absence of miR-21 limited lesion development both in the aortic sinus (by almost 30%) and in the aorta (by almost 50%). This was associated with less monocyte availability in circulation and increased apoptosis of local macrophages in plaques. At later stages of atherosclerosis, lesion size in the aortic root was similar in ApoE -/- and ApoE -/- miR-21 -/- mice, but plaques showed a less stable phenotype (larger necrotic cores) in the latter. The loss of protection in advanced stages was most likely because of excessive inflammatory apoptosis related to an impairment of local efficient efferocytosis. Conclusions- Gene deletion of miR-21 in ApoE -/- mice alters Ly-6Clo nonclassical monocytes homeostasis and contribute to limit early-stage atherosclerosis.This work was supported by Institut National de la Santé et de la Recherche Médicale

Indoleamine 2 3-dioxygenase knockout limits angiotensin II-induced aneurysm in low density lipoprotein receptor-deficient mice fed with high fat diet.

AIMS: Abdominal aortic aneurysm (AAA) is an age-associated disease characterized by chronic inflammation, vascular cell apoptosis and metalloproteinase-mediated extracellular matrix degradation. Despite considerable progress in identifying targets involved in these processes, therapeutic approaches aiming to reduce aneurysm growth and rupture are still scarce. Indoleamine 2-3 dioxygenase 1 (IDO) is the first and rate-limiting enzyme involved in the conversion of tryptophan (Trp) into kynurenine (Kyn) pathway. In this study, we investigated the role of IDO in two different models of AAA in mice. METHODS AND RESULTS: Mice with deficiencies in both low density receptor-deficient (Ldlr-/-) and IDO (Ldlr-/-Ido1-/-) were generated by cross-breeding Ido1-/- mice with Ldlr-/-mice. To induce aneurysm, these mice were infused with angiotensin II (Ang II) (1000 ng/min/kg) and fed with high fat diet (HFD) during 28 days. AAAs were present in almost all Ldlr-/- infused with AngII, but only in 50% of Ldlr-/-Ido1-/- mice. Immunohistochemistry at an early time point (day 7) revealed no changes in macrophage and T lymphocyte infiltration within the vessel wall, but showed reduced apoptosis, as assessed by TUNEL assay, and increased α-actin staining within the media of Ldlr-/-Ido1-/- mice, suggesting enhanced survival of vascular smooth muscle cells (VSMCs) in the absence of IDO. In another model of elastase-induced AAA in C57Bl/6 mice, IDO deficiency had no effect on aneurysm formation. CONCLUSION: Our study showed that the knockout of IDO prevented VSMC apoptosis in AngII -treated Ldlr-/- mice fed with HFD, suggesting a detrimental role of IDO in AAA formation and thus would be an important target for the treatment of aneurysm

The Dendritic Cell Receptor DNGR-1 Promotes the Development of Atherosclerosis in Mice.

RATIONALE: Necrotic core formation during the development of atherosclerosis is associated with a chronic inflammatory response and promotes accelerated plaque development and instability. However, the molecular links between necrosis and the development of atherosclerosis are not completely understood. Clec9a (C-type lectin receptor) or DNGR-1 (dendritic cell NK lectin group receptor-1) is preferentially expressed by the CD8α+ subset of dendritic cells (CD8α+ DCs) and is involved in sensing necrotic cells. We hypothesized that sensing of necrotic cells by DNGR-1 plays a determinant role in the inflammatory response of atherosclerosis. OBJECTIVE: We sought to address the impact of total, bone marrow-restricted, or CD8α+ DC-restricted deletion of DNGR-1 on atherosclerosis development. METHODS AND RESULTS: We show that total absence of DNGR-1 in Apoe (apolipoprotein e)-deficient mice (Apoe-/-) and bone marrow-restricted deletion of DNGR-1 in Ldlr (low-density lipoprotein receptor)-deficient mice (Ldlr-/-) significantly reduce inflammatory cell content within arterial plaques and limit atherosclerosis development in a context of moderate hypercholesterolemia. This is associated with a significant increase of the expression of interleukin-10 (IL-10). The atheroprotective effect of DNGR-1 deletion is completely abrogated in the absence of bone marrow-derived IL-10. Furthermore, a specific deletion of DNGR-1 in CD8α+ DCs significantly increases IL-10 expression, reduces macrophage and T-cell contents within the lesions, and limits the development of atherosclerosis. CONCLUSIONS: Our results unravel a new role of DNGR-1 in regulating vascular inflammation and atherosclerosis and potentially identify a new target for disease modulation

Genetic and Pharmacological Inhibition of TREM-1 Limits the Development of Experimental Atherosclerosis.

BACKGROUND: Innate immune responses activated through myeloid cells contribute to the initiation, progression, and complications of atherosclerosis in experimental models. However, the critical upstream pathways that link innate immune activation to foam cell formation are still poorly identified. OBJECTIVES: This study sought to investigate the hypothesis that activation of the triggering receptor expressed on myeloid cells (TREM-1) plays a determinant role in macrophage atherogenic responses. METHODS: After genetically invalidating Trem-1 in chimeric Ldlr-/-Trem-1-/- mice and double knockout ApoE-/-Trem-1-/- mice, we pharmacologically inhibited Trem-1 using LR12 peptide. RESULTS: Ldlr-/- mice reconstituted with bone marrow deficient for Trem-1 (Trem-1-/-) showed a strong reduction of atherosclerotic plaque size in both the aortic sinus and the thoracoabdominal aorta, and were less inflammatory compared to plaques of Trem-1+/+ chimeric mice. Genetic invalidation of Trem-1 led to alteration of monocyte recruitment into atherosclerotic lesions and inhibited toll-like receptor 4 (TLR 4)-initiated proinflammatory macrophage responses. We identified a critical role for Trem-1 in the upregulation of cluster of differentiation 36 (CD36), thereby promoting the formation of inflammatory foam cells. Genetic invalidation of Trem-1 in ApoE-/-/Trem-1-/- mice or pharmacological blockade of Trem-1 in ApoE-/- mice using LR-12 peptide also significantly reduced the development of atherosclerosis throughout the vascular tree, and lessened plaque inflammation. TREM-1 was expressed in human atherosclerotic lesions, mainly in lipid-rich areas with significantly higher levels of expression in atheromatous than in fibrous plaques. CONCLUSIONS: We identified TREM-1 as a major upstream proatherogenic receptor. We propose that TREM-1 activation orchestrates monocyte/macrophage proinflammatory responses and foam cell formation through coordinated and combined activation of CD36 and TLR4. Blockade of TREM-1 signaling may constitute an attractive novel and double-hit approach for the treatment of atherosclerosis