Hyperspectral images segmentation: a proposal

Hyper-Spectral Imaging (HIS) also known as chemical or spectroscopic imaging is an emerging technique that combines imaging and spectroscopy to capture both spectral and spatial information from an object. Hyperspectral images are made up of contiguous wavebands in a given spectral band. These images provide information on the chemical make-up profile of objects, thus allowing the differentiation of objects of the same colour but which possess make-up profile. Yet, whatever the application field, most of the methods devoted to HIS processing conduct data analysis without taking into account spatial information.Pixels are processed individually, as an array of spectral data without any spatial structure. Standard classification approaches are thus widely used (k-means, fuzzy-c-means hierarchical classification...). Linear modelling methods such as Partial Least Square analysis (PLS) or non linear approaches like support vector machine (SVM) are also used at different scales (remote sensing or laboratory applications). However, with the development of high resolution sensors, coupled exploitation of spectral and spatial information to process complex images, would appear to be a very relevant approach. However, few methods are proposed in the litterature. The most recent approaches can be broadly classified in two main categories. The first ones are related to a direct extension of individual pixel classification methods using just the spectral dimension (k-means, fuzzy-c-means or FCM, Support Vector Machine or SVM). Spatial dimension is integrated as an additionnal classification parameter (Markov fields with local homogeneity constrainst [5], Support Vector Machine or SVM with spectral and spatial kernels combination [2], geometrically guided fuzzy C-means [3]...). The second ones combine the two fields related to each dimension (spectral and spatial), namely chemometric and image analysis. Various strategies have been attempted. The first one is to rely on chemometrics methods (Principal Component Analysis or PCA, Independant Component Analysis or ICA, Curvilinear Component Analysis...) to reduce the spectral dimension and then to apply standard images processing technics on the resulting score images i.e. data projection on a subspace. Another approach is to extend the definition of basic image processing operators to this new dimensionality (morphological operators for example [1, 4]). However, the approaches mentioned above tend to favour only one description either directly or indirectly (spectral or spatial). The purpose of this paper is to propose a hyperspectral processing approach that strikes a better balance in the treatment of both kinds of information....Cet article présente une stratégie de segmentation d’images hyperspectrales liant de façon symétrique et conjointe les aspects spectraux et spatiaux. Pour cela, nous proposons de construire des variables latentes permettant de définir un sous-espace représentant au mieux la topologie de l’image. Dans cet article, nous limiterons cette notion de topologie à la seule appartenance aux régions. Pour ce faire, nous utilisons d’une part les notions de l’analyse discriminante (variance intra, inter) et les propriétés des algorithmes de segmentation en région liées à celles-ci. Le principe générique théorique est exposé puis décliné sous la forme d’un exemple d’implémentation optimisé utilisant un algorithme de segmentation en région type split and merge. Les résultats obtenus sur une image de synthèse puis réelle sont exposés et commentés

Hyperspectral image segmentation: the butterfly approach

International audienceFew methods are proposed in the litterature for coupling the spectral and the spatial dimension available on hyperspectral images. This paper proposes a generic segmentation scheme named butterfly based on an iterative process and a cross analysis of spectral and spatial information. Indeed, spatial and spatial structures are extracted in spatial and spectral space respectively both taking into account the other one. To apply this layout on hyperspectral imgages, we focus particulary on spatial and spectral structures i.e. topologic concepts and latent variable for the spatial and the spectral space respectively. Moreover, a cooperation scheme with these structures is proposed. Finally, results obtained on real hyperspectral images using this specific implementation of the butterfly approach are presented and discussed

Climate Change and Congenital Anomalies: A Population-Based Study of the Effect of Prolonged Extreme Heat Exposure on the Risk of Neural Tube Defects in France

BackgroundExposure to long-lasting extreme ambient temperatures in the periconceptional or early pregnancy period might increase the risk of neural tube defects (NTDs). We tested whether prolonged severe heat exposure as experienced during the 2003 extreme heatwave in France, affected the risk of NTDs.MethodsWe retrieved NTD cases spanning from January 1994 to December 2018 from the Paris Registry of Congenital Malformations. The 2003 heatwave was characterized by the long duration and high intensity of nine consecutive days with temperatures ≥35°C. We classified monthly conceptions occurring in August 2003 as “exposed” to prolonged extreme heat around conception (i.e., periconceptional period). We assessed whether the risk of NTDs among cohorts exposed to the prolonged severe heatwave of 2003 in the periconceptional period differed from expected values using Poisson/negative binomial regression.FindingsWe identified 1272 NTD cases from January 1994 to December 2018, yielding a monthly mean count of 4.24. Ten NTD cases occurred among births conceived in August 2003. The risk of NTD was increased in the cohort with periconceptional exposure to the August 2003 heatwave (relative risk = 2.14, 95% confidence interval: 1.46 to 3.13), compared to non-exposed cohorts. Sensitivity analyses excluding July and September months or restricting to summer months yielded consistent findings.InterpretationEvidence from the “natural experiment” of an extreme climate event suggests an elevated risk of NTDs following exposure to prolonged extreme heat during the periconceptional period

Population-based evaluation of a suggested anatomic and clinical classification of congenital heart defects based on the International Paediatric and Congenital Cardiac Code

<p>Abstract</p> <p>Background</p> <p>Classification of the overall spectrum of congenital heart defects (CHD) has always been challenging, in part because of the diversity of the cardiac phenotypes, but also because of the oft-complex associations. The purpose of our study was to establish a comprehensive and easy-to-use classification of CHD for clinical and epidemiological studies based on the long list of the International Paediatric and Congenital Cardiac Code (IPCCC).</p> <p>Methods</p> <p>We coded each individual malformation using six-digit codes from the long list of IPCCC. We then regrouped all lesions into 10 categories and 23 subcategories according to a multi-dimensional approach encompassing anatomic, diagnostic and therapeutic criteria. This anatomic and clinical classification of congenital heart disease (ACC-CHD) was then applied to data acquired from a population-based cohort of patients with CHD in France, made up of 2867 cases (82% live births, 1.8% stillbirths and 16.2% pregnancy terminations).</p> <p>Results</p> <p>The majority of cases (79.5%) could be identified with a single IPCCC code. The category "Heterotaxy, including isomerism and mirror-imagery" was the only one that typically required more than one code for identification of cases. The two largest categories were "ventricular septal defects" (52%) and "anomalies of the outflow tracts and arterial valves" (20% of cases).</p> <p>Conclusion</p> <p>Our proposed classification is not new, but rather a regrouping of the known spectrum of CHD into a manageable number of categories based on anatomic and clinical criteria. The classification is designed to use the code numbers of the long list of IPCCC but can accommodate ICD-10 codes. Its exhaustiveness, simplicity, and anatomic basis make it useful for clinical and epidemiologic studies, including those aimed at assessment of risk factors and outcomes.</p

Maternal periodontitis and the causes of preterm birth: the case-control Epipap study.

International audienceAIM: To analyse the association between maternal periodontitis and preterm birth ( or =37 weeks) at six French maternity units were included. Periodontal examinations after delivery identified localized and generalized periodontitis. Cases were classified according to four causes of preterm birth. Polytomous logistic regression analysis was used to control for confounders (maternal age, parity, nationality, educational level, marital status, employment during pregnancy, body mass index before pregnancy, smoking status) and the examiner. RESULTS: Localized periodontitis was identified in 129 (11.6%) cases and in 118 (10.8%) control women and generalized periodontitis in 148 (13.4%) and 118 (10.8%), respectively. A significant association was observed between generalized periodontitis and induced preterm birth for pre-eclampsia [adjusted odds ratio 2.46 [95% confidence intervals (95% CI)1.58-3.83]. Periodontitis was not associated with spontaneous preterm birth or preterm premature rupture of membranes or with the other causes. CONCLUSION: Maternal periodontitis is associated with an increased risk of induced preterm birth due to pre-eclampsia

Metformin exposure in first trimester of pregnancy and risk of all or specific congenital anomalies: exploratory case-control study

To investigate whether exposure to metformin during the first trimester of pregnancy, for diabetes or other indications, increases the risk of all or specific congenital anomalies. Population based exploratory case-control study using malformed controls. Cases of 29 specific subgroups of non-genetic anomalies, and all non-genetic anomalies combined, were compared with controls (all other non-genetic anomalies or genetic syndromes). 11 EUROmediCAT European congenital anomaly registries surveying 1 892 482 births in Europe between 2006 and 2013. 50 167 babies affected by congenital anomaly (41 242 non-genetic and 8925 genetic) including live births, fetal deaths from 20 weeks' gestation, and terminations of pregnancy for fetal anomaly. Odds ratios adjusted for maternal age, registry, multiple birth, and maternal diabetes status. 168 babies affected by congenital anomaly (141 non-genetic and 27 genetic) were exposed to metformin, 3.3 per 1000 births. No evidence was found for a higher proportion of exposure to metformin during the first trimester among babies with all non-genetic anomalies combined compared with genetic controls (adjusted odds ratio 0.84, 95% confidence interval 0.55 to 1.30). The only significant result was for pulmonary valve atresia (adjusted odds ratio 3.54, 1.05 to 12.00, compared with non-genetic controls; 2.86, 0.79 to 10.30, compared with genetic controls). No evidence was found for an increased risk of all non-genetic congenital anomalies combined following exposure to metformin during the first trimester, and the one significant association was no more than would be expected by chance. Further surveillance is needed to increase sample size and follow up the cardiac signal, but these findings are reassuring given the increasing use of metformin in pregnancy

Risk factors for mortality in infancy and childhood in children with major congenital anomalies: a European population-based cohort study

BACKGROUND: Preterm birth and young maternal age are known risk factors for infant and childhood mortality. There is limited knowledge of the impact of these risk factors in children born with major congenital anomalies (CAs), who have inherently higher risks of death compared with other children.OBJECTIVES: To investigate the risk factors for mortality up to age 10 years in children born with specific major CAs.METHODS: This population-based cohort study involved 150,198 livebirths from 1995 to 2014 in 13 European CA registries linked to mortality data. Cox proportional hazards models estimated the association of gestational age, maternal age and child's sex with death &lt;1 year and 1-9 years for the whole cohort and by CA subgroup. Hazard ratios (HR) from each registry were pooled using multivariate meta-analysis.RESULTS: Preterm birth had a dose-response association with mortality; compared with infants born at 37+ weeks gestation, those born at &lt;28, 28-31 and 32-36 weeks had 14.88 (95% CI 12.57, 17.62), 8.39 (95% CI 7.16, 9.85) and 3.88 (95% CI 3.40, 4.43) times higher risk of death &lt;1 year, respectively. The corresponding risks at 1-9 years were 4.99 (95% CI 2.94, 8.48), 3.09 (95% CI 2.28, 4.18) and 2.04 (95% CI 1.69, 2.46) times higher, respectively. Maternal age &lt;20 years (versus 20-34 years) was a risk factor for death &lt;1 year (HR 1.30, 95% CI 1.09, 1.54) and 1-9 years (HR 1.58, 95% CI 1.19, 2.10). Females had 1.22 (95% CI: 1.07, 1.39) times higher risk of death between 1 and 9 years than males.CONCLUSION: Preterm birth was associated with considerably higher infant and childhood mortality in children with CAs, comparable to estimates reported elsewhere for the background population. Additional risk factors included young maternal age and female sex. Information on risk factors could benefit clinical care and guide counselling of parents following CA diagnoses.</p