A Replica Inference Approach to Unsupervised Multi-Scale Image Segmentation

We apply a replica inference based Potts model method to unsupervised image segmentation on multiple scales. This approach was inspired by the statistical mechanics problem of "community detection" and its phase diagram. Specifically, the problem is cast as identifying tightly bound clusters ("communities" or "solutes") against a background or "solvent". Within our multiresolution approach, we compute information theory based correlations among multiple solutions ("replicas") of the same graph over a range of resolutions. Significant multiresolution structures are identified by replica correlations as manifest in information theory overlaps. With the aid of these correlations as well as thermodynamic measures, the phase diagram of the corresponding Potts model is analyzed both at zero and finite temperatures. Optimal parameters corresponding to a sensible unsupervised segmentation correspond to the "easy phase" of the Potts model. Our algorithm is fast and shown to be at least as accurate as the best algorithms to date and to be especially suited to the detection of camouflaged images.Comment: 26 pages, 22 figure

Deciphering the nitrate signaling pathway leading to a reduction of primary root growth in Medicago truncatula

In the model legume Medicago truncatula, nitrate has been shown to inhibit primary root growth through the reduction of root cell elongation. Nitrate, as an essential nutrient, also acts as a signal molecule that is sensed and transduced through a nitrate transporter MtNPF6.8, with RNAi mutants deficient in MtNPF6.8 being insensitive to nitrate [1, 2]. We tested here whether reactive oxygen species (ROS) could be downstream mediators of the nitrate signal since ROS are able to transduce ABA signal in other contexts and also govern the primary root growth. Thus, we analyzed the distribution of ROS (H2O2, O2•−, •OH) and peroxidase activity all along the primary root of seedlings sensitive or insensitive to nitrate using different genotypes of M. truncatula, three wild types and a npf6.8RNAi mutant grown with or without nitrate, to determine whether nitrate modifies ROS and peroxidase patterns. We found that nitrate modified the morphology of the root tip, induced an increase in H2O2, and a decrease in O2•− and •OH in seedlings sensitive to nitrate (R108, A17, and DZA315-16), but not in seedlings insensitive to nitrate (npf6.8RNAi mutant). These results suggest that ROS and peroxidases are downstream mediators in the nitrate signaling pathway. The origin of the change in ROS accumulation in response to nitrate was further investigated following the activity of major enzymes (peroxidase, SOD, Nox) able to interfere with ROS accumulation

Long non-coding RNAs as local regulators of pancreatic islet transcription factor genes

The transcriptional programs of differentiated cells are tightly regulated by interactions between cell type-specific transcription factors and cis-regulatory elements. Long non-coding RNAs (lncRNAs) have emerged as additional regulators of gene transcription. Current evidence indicates that lncRNAs are a very heterogeneous group of molecules. For example, selected lncRNAs have been shown to regulate gene expression in cis or trans, although in most cases the precise underlying molecular mechanisms is unknown. Recent studies have uncovered a large number of lncRNAs that are selectively expressed in pancreatic islet cells, some of which were shown to regulate β cell transcriptional programs. A subset of such islet lncRNAs appears to control the expression of β cell-specific transcription factor (TF) genes by local cis-regulation. In this review, we discuss current knowledge of molecular mechanisms underlying cis-regulatory lncRNAs and discuss challenges involved in using genetic perturbations to define their function. We then discuss known examples of pancreatic islet lncRNAs that appear to exert cis-regulation of TF genes. We propose that cis-regulatory lncRNAs could represent a molecular target for modulation of diabetes-relevant genes

On morphological hierarchical representations for image processing and spatial data clustering

Hierarchical data representations in the context of classi cation and data clustering were put forward during the fties. Recently, hierarchical image representations have gained renewed interest for segmentation purposes. In this paper, we briefly survey fundamental results on hierarchical clustering and then detail recent paradigms developed for the hierarchical representation of images in the framework of mathematical morphology: constrained connectivity and ultrametric watersheds. Constrained connectivity can be viewed as a way to constrain an initial hierarchy in such a way that a set of desired constraints are satis ed. The framework of ultrametric watersheds provides a generic scheme for computing any hierarchical connected clustering, in particular when such a hierarchy is constrained. The suitability of this framework for solving practical problems is illustrated with applications in remote sensing

Liver segmentation in MRI: a fully automatic method based on stochastic partitions

There are few fully automated methods for liver segmentation in magnetic resonance images (MRI) despite the benefits of this type of acquisition in comparison to other radiology techniques such as computed tomography (CT). Motivated by medical requirements, liver segmentation in MRI has been carried out. For this purpose, we present a new method for liver segmentation based on the watershed transform and stochastic partitions. The classical watershed over-segmentation is reduced using a marker-controlled algorithm. To improve accuracy of selected contours, the gradient of the original image is successfully enhanced by applying a new variant of stochastic watershed. Moreover, a final classifier is performed in order to obtain the final liver mask. Optimal parameters of the method are tuned using a training dataset and then they are applied to the rest of studies (17 datasets). The obtained results (a Jaccard coefficient of 0.91 +/- 0.02) in comparison to other methods demonstrate that the new variant of stochastic watershed is a robust tool for automatic segmentation of the liver in MRI. (C) 2014 Elsevier Ireland Ltd. All rights reserved.This work has been supported by the MITYC under the project NaRALap (ref. TSI-020100-2009-189), partially by the CDTI under the project ONCOTIC (IDI-20101153), by Ministerio de Educacion y Ciencia Spain, Project Game Teen (TIN2010-20187) projects Consolider-C (SEJ2006-14301/PSIC), "CIBER of Physiopathology of Obesity and Nutrition, an initiative of ISCIII" and Excellence Research Program PROMETEO (Generalitat Valenciana. Conselleria de Educacion, 2008-157). We would like to express our gratitude to the Hospital Clinica Benidorm, for providing the MR datasets and to the radiologist team of Inscanner for the manual segmentation of the MR images.López-Mir, F.; Naranjo Ornedo, V.; Angulo, J.; Alcañiz Raya, ML.; Luna, L. (2014). Liver segmentation in MRI: a fully automatic method based on stochastic partitions. Computer Methods and Programs in Biomedicine. 114(1):11-28. https://doi.org/10.1016/j.cmpb.2013.12.022S1128114

Semi-automatic algorithm for construction of the left ventricular area variation curve over a complete cardiac cycle

<p>Abstract</p> <p>Background</p> <p>Two-dimensional echocardiography (2D-echo) allows the evaluation of cardiac structures and their movements. A wide range of clinical diagnoses are based on the performance of the left ventricle. The evaluation of myocardial function is typically performed by manual segmentation of the ventricular cavity in a series of dynamic images. This process is laborious and operator dependent. The automatic segmentation of the left ventricle in 4-chamber long-axis images during diastole is troublesome, because of the opening of the mitral valve.</p> <p>Methods</p> <p>This work presents a method for segmentation of the left ventricle in dynamic 2D-echo 4-chamber long-axis images over the complete cardiac cycle. The proposed algorithm is based on classic image processing techniques, including time-averaging and wavelet-based denoising, edge enhancement filtering, morphological operations, homotopy modification, and watershed segmentation. The proposed method is semi-automatic, requiring a single user intervention for identification of the position of the mitral valve in the first temporal frame of the video sequence. Image segmentation is performed on a set of dynamic 2D-echo images collected from an examination covering two consecutive cardiac cycles.</p> <p>Results</p> <p>The proposed method is demonstrated and evaluated on twelve healthy volunteers. The results are quantitatively evaluated using four different metrics, in a comparison with contours manually segmented by a specialist, and with four alternative methods from the literature. The method's intra- and inter-operator variabilities are also evaluated.</p> <p>Conclusions</p> <p>The proposed method allows the automatic construction of the area variation curve of the left ventricle corresponding to a complete cardiac cycle. This may potentially be used for the identification of several clinical parameters, including the area variation fraction. This parameter could potentially be used for evaluating the global systolic function of the left ventricle.</p

Parent satisfaction with the Loire Infant Follow-up Team (LIFT) premature and at-risk infant network in the Pays-de-la-Loire area (France)

BACKGROUND: The Loire Infant Follow-up Team (LIFT) is a network for caring for premature infants whose gestational age is 34 WA or less and at-risk neonates in the Pays-de-la-Loire area in France. The network aims to screen for clinical anomalies early and to propose adapted care. Trained physicians follow the included children in a standardized manner at 3, 6, 9, 12, and 18 months and 2 years, with a specific examination by psychologists at 2 years. The aim of the study was to assess the satisfaction of the parents of the children followed.METHODS: To evaluate parent satisfaction, a questionnaire from the Consumer Satisfaction Survey (CSS) in its French version was sent to parents whose infants were 2 years old, stratifying on the presence of an anomaly. The questioner had 39 items, with 8 specific items on the network and 31 from the CSS. The questionnaire was mailed twice in September 2006. RESULTS: Out of 300 questionnaires mailed, 269 were returned (rate 89.7 %). The questionnaire was assessed using principal component analysis with 2 dimensions for the 30 items common to all children, one of which covered empathy with physicians and the other with the consulting psychologists at 2 years. The validity was good (Cronbach coefficient, 0.91). The answers to overall questions such as "We are satisfied with the care in the network" scored 16.1±0.7/20, with 90 % "totally agree" or "moderately agree" responses. The "The care is perfect" scored 14.6±0.7/20 with 78 % agreeing with the statement. The total score for 30 general questions was 14.6±3.1 (median, 14.9). The total score was lower for infants with anomalies: 13.7±3.3 versus 14.9±2.9 (P&lt;0.01). The answers with a low score (&lt;10) were given by 22 parents (8.2 %). There was no significant relation between the total score or the satisfaction score and neonatal events. CONCLUSION: A postal survey is helpful to know the views of parents on the follow-up of their infants. This good level of satisfaction seems to stem from the parents feeling they belong to the network, the quality of the relationships with personnel, and the doctors\u27 empathy, as well as the number of contacts between parents and the network coordinator

Longitudinal Follow-up of Chronic Pulmonary Manifestations in Esophageal Atresia: A Clinical Algorithm and Review of the Literature

In the past decades improved surgical techniques and better neonatal supportive care have resulted in reduced mortality of patients with esophageal atresia (EA), with or without tracheoesophageal fistula, and in increased prevalence of long-term complications, especially respiratory manifestations. This integrative review describes the techniques currently used in the pediatric clinical practice for assessing EA-related respiratory disease. We also present a novel algorithm for the evaluation and surveillance of lung disease in EA. A total of 2813 articles were identified, of which 1451 duplicates were removed, and 1330 were excluded based on review of titles and abstracts. A total of 32 articles were assessed for eligibility. Six reviews were excluded, and 26 original studies were assessed. Lower respiratory tract infection seems frequent, especially in the first years of life. Chronic asthma, productive cough, and recurrent bronchitis are the most common respiratory complaints. Restrictive lung disease is generally reported to prevail over the obstructive or mixed patterns, and, overall, bronchial hyperresponsiveness can affect up to 78% of patients. At lung imaging, few studies detected bronchiectasis and irregular cross-sectional shape of the trachea, whereas diffuse bronchial thickening, consolidations, and pleural abnormalities were the main chest X-ray findings. Airway endoscopy is seldom included in the available studies, with tracheomalacia and tracheobronchial inflammation being described in a variable proportion of cases. A complete diagnostic approach to long-term respiratory complications after EA is mandatory. In the presence of moderate-to-severe airway disease, patients should undergo regular tertiary care follow-up with functional assessment and advanced chest imaging