Optimization of Divergences Within the Exponential Family for Image Segmentation

International audienceIn this work, we propose novel results for the optimization of divergences within the framework of region-based active contours. We focus on parametric statistical models where the region descriptor is chosen as the probability density function (pdf) of an image feature (e.g. intensity) inside the region and the pdf belongs to the exponential family. The optimization of divergences appears as a flexible tool for segmentation with and without intensity prior. As far as segmentation without reference is concerned, we aim at maximizing the discrepancy between the pdf of the inside region and the pdf of the outside region. Moreover, since the optimization framework is performed within the exponential family, we can cope with difficult segmentation problems including various noise models (Gaussian, Rayleigh, Poisson, Bernoulli ...). We also experimentally show that the maximisation of the KL divergence offers interesting properties compare to some other data terms (e.g. minimization of the anti-log-likelihood). Experimental results on medical images (brain MRI, contrast echocardiography) confirm the applicability of this general setting

PDEs for tensor image processing

Methods based on partial differential equations (PDEs) belong to those image processing techniques that can be extended in a particularly elegant way to tensor fields. In this survey paper the most important PDEs for discontinuity-preserving denoising of tensor fields are reviewed such that the underlying design principles becomes evident. We consider isotropic and anisotropic diffusion filters and their corresponding variational methods, mean curvature motion, and selfsnakes. These filters preserve positive semidefiniteness of any positive semidefinite initial tensor field. Finally we discuss geodesic active contours for segmenting tensor fields. Experiments are presented that illustrate the behaviour of all these methods

Efficacy and safety of preoperative preparation with Lugol''s iodine solution in euthyroid patients with Graves’ disease (LIGRADIS Trial): Study protocol for a multicenter randomized trial

Background: Currently, both the American Thyroid Association and the European Thyroid Association recommend preoperative preparation with Lugol''s Solution (LS) for patients undergoing thyroidectomy for Graves’ Disease (GD), but their recommendations are based on low-quality evidence. The LIGRADIS trial aims to provide evidence either to support or refute the systematic use of LS in euthyroid patients undergoing thyroidectomy for GD. Methods: A multicenter randomized controlled trial will be performed. Patients =18 years of age, diagnosed with GD, treated with antithyroid drugs, euthyroid and proposed for total thyroidectomy will be eligible for inclusion. Exclusion criteria will be prior thyroid or parathyroid surgery, hyperparathyroidism that requires associated parathyroidectomy, thyroid cancer that requires adding a lymph node dissection, iodine allergy, consumption of lithium or amiodarone, medically unfit patients (ASA-IV), breastfeeding women, preoperative vocal cord palsy and planned endoscopic, video-assisted or remote access surgery. Between January 2020 and January 2022, 270 patients will be randomized for either receiving or not preoperative preparation with LS. Researchers will be blinded to treatment assignment. The primary outcome will be the rate of postoperative complications: hypoparathyroidism, recurrent laryngeal nerve injury, hematoma, surgical site infection or death. Secondary outcomes will be intraoperative events (Thyroidectomy Difficulty Scale score, blood loss, recurrent laryngeal nerve neuromonitoring signal loss), operative time, postoperative length of stay, hospital readmissions, permanent complications and adverse events associated to LS. Conclusions: There is no conclusive evidence supporting the benefits of preoperative treatment with LS in this setting. This trial aims to provide new insights into future Clinical Practice Guidelines recommendations. Trial registration: ClinicalTrials.gov identifier: NCT03980132. © 202

Wetlands for wastewater treatment and subsequent recycling of treated effluent : a review

Due to water scarcity challenges around the world, it is essential to think about non-conventional water resources to address the increased demand in clean freshwater. Environmental and public health problems may result from insufficient provision of sanitation and wastewater disposal facilities. Because of this, wastewater treatment and recycling methods will be vital to provide sufficient freshwater in the coming decades, since water resources are limited and more than 70% of water are consumed for irrigation purposes. Therefore, the application of treated wastewater for agricultural irrigation has much potential, especially when incorporating the reuse of nutrients like nitrogen and phosphorous, which are essential for plant production. Among the current treatment technologies applied in urban wastewater reuse for irrigation, wetlands were concluded to be the one of the most suitable ones in terms of pollutant removal and have advantages due to both low maintenance costs and required energy. Wetland behavior and efficiency concerning wastewater treatment is mainly linked to macrophyte composition, substrate, hydrology, surface loading rate, influent feeding mode, microorganism availability, and temperature. Constructed wetlands are very effective in removing organics and suspended solids, whereas the removal of nitrogen is relatively low, but could be improved by using a combination of various types of constructed wetlands meeting the irrigation reuse standards. The removal of phosphorus is usually low, unless special media with high sorption capacity are used. Pathogen removal from wetland effluent to meet irrigation reuse standards is a challenge unless supplementary lagoons or hybrid wetland systems are used