There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

This paper describes the ATLAS experiment as installed in i ts experimental cavern at point 1 at CERN. It also presents a brief overview of the expec ted performance of the detector.

http://absimage.aps.org/image/SES08/MWS_SES08-2008-020010.pdf

The ATLAS Experiment at the CERN Large Hadron Collider

Crop diseases are a major threat to food security, but their rapid identification remains difficult in many parts of the world due to the lack of the necessary infrastructure. The combination of increasing global smartphone penetration and recent advances in computer vision made possible by deep learning has paved the way for smartphone-assisted disease diagnosis. Using a public dataset of 54,306 images of diseased and healthy plant leaves collected under controlled conditions, we train a deep convolutional neural network to identify 14 crop species and 26 diseases (or absence thereof). The trained model achieves an accuracy of 99.35% on a held-out test set, demonstrating the feasibility of this approach. Overall, the approach of training deep learning models on increasingly large and publicly available image datasets presents a clear path toward smartphone-assisted crop disease diagnosis on a massive global scale.

/pdf/using-deep-learning-for-image-based-plant-disease-detection-3ep7b222h5.pdf

Using Deep Learning for Image-Based Plant Disease Detection

MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

Course Description This is an advanced course in which we explore the field of Statistical Optics. Topics covered include such subjects as the statistical properties of natural (thermal) and laser light, spatial and temporal coherence, effects of partial coherence on optical imaging instruments, effects on imaging due to randomly inhomogeneous media, and a statistical treatment of the detection of light. Development of this more comprehensive model of the behavior of light draws upon the use of tools traditionally available to the electrical engineer, such as linear system theory and the theory of stochastic processes.

http://ieeexplore.ieee.org/iel5/3/23094/01073023.pdf

Statistical optics

Periodic thermal imaging is a method of active thermography based on a periodic thermal stimulation of an inspected sample material and the analysis of its thermal response when a steady regime is reached. The original data, a sequence of images sampling the thermal response on a large number of periods, are usually stored in a raw format. For accurate exploitation of these measurements, the whole sequence of images requires a significant amount of storage space. In this report, we address the question of the lossy compression of these sequences of images when they are applied to perform physical parameter estimation. The study investigates the impact of lossy image compression on the performance of the physical parameter estimation procedure, and shows the possibility of preserving robust estimation with high compression rate. Perspectives and applications are then discussed. Performing good enough estimate of physical parameters with compressed images would permit the use of portable thermal cameras with limited resources in terms of data storage. This would enable the use of periodic active thermal imaging to perform relatively low cost embedded characterization of thermal properties of materials.

/pdf/impact-of-a-lossy-image-compression-on-parameter-estimation-3nlrl35ghj.pdf

Impact of a lossy image compression on parameter estimation with periodic active thermal imaging

Spectres multifractals de signaux laser Doppler acquis au cours d'un chauffage cutané local

Context: Gliomas account for 80% of malignant primitive tumors of the central nervous system. It is the most common primary brain tumor in adults, with a median age at diagnosis of 64 years. They are infiltrative cancers and are often not curable. Surgery is the first step to treat gliomas and studies have shown that the survival rate is linked with the quality of the surgery. Thus, it is mandatory to get the most extended resection. Today, 5-ALA-induced protoporphyrin IX (PpIX) fluorescence is widely used to help the surgeon distinguish infiltrative compound of gliomas. The current methods are based on intraoperative surgical fluorescence microscopy or optical fiber systems that allow a local emission spectrum measurement or a quantification of 5-ALA-induced PpIX concentration. However, the accuracy of such technics remains limited because of a still low sensitivity to evaluate infiltrative compound of gliomas.We demonstrated in a previous in vitro and ex vivo study that the PpIX spectrum is more complex than expected. Biopsies were from patients with glioblastomas (GBM), which are high grade gliomas. We showed that, added to the known peak at 634 nm (PpIX634), a second peak appears sometimes at 620 nm (PpIX620). We assumed that those two peaks correspond to two states of PpIX, which depend on the microenvironment. Knowing this, we proposed new measured parameters to distinguish the solid component of GBM from low grade gliomas and infiltrative component of GBM [10]. Figure 1 shows the ratio between the two states and discrimination of the solid component of GBM.Our goal is then to create an intraoperative tool based on fluorescence spectroscopy to assist the surgeon during tumor’s margins resection. This paper focuses on new instrumental development to distinguish the two states of PpIX, based on multi-wavelength excitation.

https://hal.archives-ouvertes.fr/hal-01180039/document

Spectroscopic fluorescence measurements as an intraoperative tool for glioma resection

La creation de varietes presentant un niveau de resistance fort et durable passe immanquablement par la mise en œuvre de methodes de phenotypage toujours plus discriminantes, reproductibles et pouvant etre mises en œuvre sur de grands effectifs. Les methodes actuelles de phenotypage font encore tres souvent appel a une notation visuelle des symptomes. Nous rapportons ici la mise en œuvre de differentes methodes de phenotypage alternatives permettant de caracteriser, soit la phase asymptomatique par l’utilisation de nouvelles technologies telles que la qPCR, la thermographie ou la mesure de fluorescence de chlorophylle, soit la phase symptomatique a l’aide de tests en conditions controlees. Les avantages et les limites de ces methodes sont abordes.

https://hal.univ-angers.fr/hal-02516459/document

Etude de la résistance partielle de la carotte à Alternaria dauci par une approche de phénotypage multi critères

The optical Doppler effect resulting from interactions between laser light photons and red blood cells of the microcirculation is used to characterize the influence of isoflurane, an halogenated volatile anesthetic, on the peripheral cardiovascular system. After having recorded laser Doppler flowmetry blood perfusion signals on isoflurane-induced anesthetized healthy rats, wavelet analyses show a significant decrease of the myogenic and neurogenic activities when isoflurane dose increases from 1.5% to 3%. Moreover, the approximate entropy shows a weak decrease of signal irregularity when dose of isoflurane increases. These findings demonstrate the usefulness of the optical Doppler effect in physiological and pharmacological applications.

David Rousseau

Papers

Impact of a lossy image compression on parameter estimation with periodic active thermal imaging

Spectres multifractals de signaux laser Doppler acquis au cours d'un chauffage cutané local

Spectroscopic fluorescence measurements as an intraoperative tool for glioma resection

Etude de la résistance partielle de la carotte à Alternaria dauci par une approche de phénotypage multi critères

Laser Doppler flowmetry signals to quantify effects of isoflurane on the peripheral cardiovascular system of healthy rats