A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Analyse de diagnostics et traitements proposés en pédiatrie ambulatoire libérale et hospitalière. Etude transversale sur une semaine dans le canton de Neuchâtel.

Le type d'affections rencontrées en pédiatrie générale ambulatoire traduit partiellement, d'une part, les compétences du pédiatre qui les prend en charge et, d'autre part, indirectement les besoins de la population en terme de soins pédiatriques. Il est utile de décrire le profil de ces affections pour plusieurs raisons ; en terme de santé publique, une connaissance du recours aux soins pédiatriques permet de mieux planifier la formation des futurs pédiatres en suivant les besoins de la population ; en terme de politique de formation, ces données permettent d'assurer un cursus éducatif de qualité adapté aux types de pathologies pédiatriques locales ; finalement, la description détaillée de l'activité de pédiatrie générale ambulatoire permet aux jeunes médecins de mieux se projeter et de s'identifier à cette profession en tant que futurs pédiatres. Il n'existe actuellement à notre connaissance que peu de données concernant les affections ambulatoires en pédiatrie de premier recours en Suisse romande ; de même, la proportion de consultations de pédiatrie ayant comme motif une pathologie infectieuse ou encore la fréquence du recours à l'antibiothérapie lors de ces dernières est méconnue en Suisse romande.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

Active mitral ring for post-surgical remote correction of residual mitral regurgitation on the beating heart.

OBJECTIVES: Residual mitral regurgitation after valve repair worsens patients' clinical outcome. Postimplant adjustable mitral rings potentially address this issue, allowing the reshaping of the annulus on the beating heart under echocardiography control. We developed an original mitral ring allowing valve geometry remodelling after the implantation and designed an animal study to assess device effectiveness in correcting residual mitral regurgitation. METHODS: The device consists of two concentric rings: one internal and flexible, sutured to the mitral annulus and a second external and rigid. A third conic element slides between the two rings, modifying the shape of the flexible ring. This sliding element is remotely activated with a rotating tool. Animal model: in adult swine, under cardio pulmonary bypass and cardiac arrest, we shortened the primary chordae of P2 segment to reproduce Type III regurgitation and implanted the active ring. We used intracardiac ultrasound to assess mitral regurgitation and the efficacy of the active ring to correct it. RESULTS: Severe mitral regurgitation (3+ and 4+) was induced in eight animals, 54 ± 6 kg in weight. Vena contracta width decreased from 0.8 ± 0.2 to 0.1 cm; proximal isovelocity surface area radius decreased from 0.8 ± 0.2 to 0.1 cm and effective regurgitant orifice area decreased from 0.50 ± 0.1 to 0.1 ± 0.1 cm(2). Six animals had a reversal of systolic pulmonary flow that normalized following the activation of the device. All corrections were reversible. CONCLUSIONS: Postimplant adjustable mitral ring corrects severe mitral regurgitation through the reversible modification of the annulus geometry on the beating heart. It addresses the frequent and morbid issue of recurrent mitral valve regurgitation.

Neues aus Diagnostik und Therapie der spinalen Erkrankungen [Novel aspects of diagnostics and therapy of spinal cord diseases].

BACKGROUND: Both non-traumatic and traumatic spinal cord injuries have in common that a relatively minor structural lesion can cause profound sensorimotor and autonomous dysfunction. Besides treating the cause of the spinal cord injury the main goal is to restore lost function as far as possible. AIM: This article provides an overview of current innovative diagnostic (imaging) and therapeutic approaches (neurorehabilitation and neuroregeneration) aiming for recovery of function after non-traumatic and traumatic spinal cord injuries. MATERIAL AND METHODS: An analysis of the current scientific literature regarding imaging, rehabilitation and rehabilitation strategies in spinal cord disease was carried out. RESULTS: Novel magnetic resonance imaging (MRI) based techniques (e.g. diffusion-weighted MRI and functional MRI) allow visualization of structural reorganization and specific neural activity in the spinal cord. Robotics-driven rehabilitative measures provide training of sensorimotor function in a targeted fashion, which can even be continued in the homecare setting. From a preclinical point of view, defined stem cell transplantation approaches allow for the first time robust structural repair of the injured spinal cord. CONCLUSION: Besides well-established neurological and functional scores, MRI techniques offer the unique opportunity to provide robust and reliable "biomarkers" for restorative therapeutic interventions. Function-oriented robotics-based rehabilitative interventions alone or in combination with stem cell based therapies represent promising approaches to achieve substantial functional recovery, which go beyond current rehabilitative treatment efforts.

L'exploitation des eaux souterraines en Syrie centrale : construction de diagnostics et politiques d'intervention

Syrian dry areas have been for several millennia a place of interaction between human populations and the environment. If environmental constraints and heterogeneity condition the human occupation and exploitation of resources, socio-political, economic and historical elements play a fundamental role. Since the late 1980s, Syrian dry areas are viewed as suffering a serious water crisis, due to groundwater overdraft. The Syrian administration and international development agencies believe that groundwater overexploitation is also leading to a decline of agricultural activities and to poverty increase. Action is thus required to address these problems.However, the overexploitation diagnosis needs to be reviewed. The overexploitation discourse appears in the context of Syria's opening to international organizations and to the market economy. It echoes the international discourse of "global water crisis". The diagnosis is based on national indicators recycling old Soviet data that has not been updated. In the post-Soviet era, the Syrian national water policy seems to abandon large surface water irrigation projects in favor of a strategy of water use rationalization and groundwater conservation in crisis regions, especially in the district of Salamieh.This groundwater conservation policy has a number of inconsistencies. It is justified for the administration and also probably for international donors, since it responds to an indisputable environmental emergency. However, efforts to conserve water are anecdotal or even counterproductive. The water conservation policy appears a posteriori as an extension of the national policy of food self-sufficiency. The dominant interpretation of overexploitation, and more generally of the water crisis, prevents any controversary approach of the status of resources and of the agricultural system in general and thus destroys any attempt to discuss alternatives with respect to groundwater management, allocation, and their inclusion in development programs.A revisited diagnosis of the situation needs to take into account spatial and temporal dimensions of the groundwater exploitation and to analyze the co-evolution of hydrogeological and agricultural systems. It should highlight the adjustments adopted to cope with environmental and economic variability, changes of water availability and regulatory measures enforcements. These elements play an important role for water availability and for the spatial, temporal, sectoral allocation of water resource. The groundwater exploitation in the last century has obviously had an impact on the environment, but the changes are not necessarily catastrophic.The current groundwater use in central Syria increases the uncertainty by reducing the ability of aquifers to buffer climatic changes. However, the climatic factor is not the only source of uncertainty. The high volatility of commodity prices, fuel, land and water, depending on the market but also on the will (and capacity) of the Syrian State to preserve social peace is a strong source of uncertainty. The research should consider the whole range of possibilities and propose alternatives that take into consideration the risks they imply for the water users, the political will to support or not the local access to water - thus involving a redefinition of the economic and social objectives - and finally the ability of international organizations to reconsider pre-established diagnoses.

Devant une plaie des membres inférieurs, quels diagnostics évoquer?

L'ulcère des membres inférieurs se définit comme une plaie située sur la partie déclive des membres inférieurs évoluant depuis plus d'un mois sans tendance à la cicatrisation spontanée. La lenteur de guérison d'un ulcère ne s'explique pas seulement par sa taille et sa profondeur mais également par l'existence d'une pathologie sous-jacente qui doit mener à un traitement spécifique pour induire la guérison de la plaie. La prévalence de l'ulcère des membres inférieurs toutes causes confondues est de 1 % dans la population générale. Une origine vasculaire est retrouvée dans la majorité des cas. On retrouve plus rarement une origine infectieuse, dermatologique, hématologique, tumorale, métabolique, neurologique, iatrogène ou traumatique. Il est essentiel de connaître l'ensemble des pathologies pouvant amener à l'ulcère de jambe afin de pouvoir assurer une prise en charge adaptée qui seule permettra d'amener à la guérison.

Self-expanding mini-cannula for remote perfusion with pediatric scenarios.

The aim of this report is to address the benefits of the minimal invasive venous drainage in a pediatric cardio surgical scenario. Juvenile bovine experiments (67.4+/-11 kg) were performed. The right atrium was cannulated in a trans-jugular way by using the self-expandable (Smart Stat, 12/20F, 430 mm) venous cannula (Smartcannula LLC, Lausanne, Switzerland) vs. a 14F 250 mm (Polystan Lighthouse) standard pediatric venous cannula. Establishing the cardiopulmonary bypass (CPB), the blood flows were assessed for 20 mmHg, 30 mmHg and 40 mmHg of driving pressure. Venous drainage (flow in l/min) at 20 mmHg, 30 mmHg, and 40 mmHg drainage load was 0.26+/-0.1, 0.35+/-0.2 and 0.28+/-0.08 for the 14F standard vs. 1.31+/-0.22, 1.35+/-0.24 and 1.9+/-0.2 for the Smart Stat 12/20F cannula. The 43 cm self-expanding 12/20F Smartcannula outperforms the 14F standard cannula. The results described herein allow us to conclude that usage of the self-expanding Smartcannula also in the pediatric patients improves the flow and the drainage capacity, avoiding the insufficient and excessive drainage. We believe that similar results may be expected in the clinical settings.

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.