Dental, Occlusal, and Craniofacial Features of Children With Microcephaly Due to Congenital Zika Infection: 3 Cases Report From Valle del Cauca, Cali—Colombia—2020

Objective: Describes dental, occlusal, and craniofacial characteristics of 3 children aged 3 to 4 years with microcephaly due to congenital Zika infection in Cali Valle del Cauca, 2020. Design: Three children case report with congenital Zika virus microcephaly. Setting: Institutional Patients: Three children with maternal viral infection confirmed by polymerase chain reaction during first trimester of pregnancy were included and were born from 2016 to 2017. Interventions: Oral and mouth functional examination was performed including soft tissue examination; lingual and labial frenulum; evaluation of swallowing and chewing; craniofacial analysis; dimension of dental arch; intercanine and intermolar distance, palate form; relationship and growth of maxilla, mandible, and facial dental midline using plaster models; and complementary image analysis. Main Outcome Measures: Child and mother sociodemographic features, craniofacial measurements; dental and oral features; maxillary and mandibular measures; and speech, swallowing, and chewing disorders. Results: Small head circumference at birth and at the time of clinical evaluation was compared to normal children of approximately their age. Upper third of the face was short, and presence of hypertonic masticatory muscles with hypotonic swallowing muscles, dysphagia, dyslalia, bruxism, lip incompetence, tongue interposition, and hypersalivation and epilepsy were the main medical problem. They have complete primary dentition with normal dental morphology, tooth eruption altered, dental caries, and dental malocclusion was identified. Conclusion: There are no changes in the dental formula and dental morphology in the deciduous dentition. They present severe chewing and speaking limitation, facial disproportion, and occlusal problems that warrant dental and medical attention.

Median-Tree: An Efficient Counterpart of Tree-of-Shapes

Representing an image through a tree structure as provided with a morphological hierarchy enables efficient image analysis and processing methods operating directly on the tree structure. Max-tree and min-tree can be built with efficient algorithms but they only focus on brighter and darker components of the image respectively. Conversely, the Tree-of-Shapes is a self-complementary image representation that provides access to all regional extrema of the image (both brighter and darker components), but its computation is more time-consuming. In this paper, we introduce a new, simple and efficient tree structure called median-tree. It relies on a median image that is straightforwardly constructed by subtracting the median pixel value from an image to decompose it into positive and negative parts. The median tree can then be obtained by applying the efficient max-tree algorithms available in the literature on this median image. We show through theoretical and experimental studies that the median-tree offers similar characteristics to the Tree-of-Shapes, but comes with a considerably lower construction complexity.

Complementary Approach for Image Edge Detection Using Rough Mirror Mapping in Neural Network

In this paper, a complementary approach has applied to obtain the available edges in the image. The complementary image has obtained by subtracting the rough mirror mapped image from the input image. The universal approximation capability of feedforward neural network has applied to define the rough mirror mapping. Multilayer perceptron network and radial basis function network have considered obtaining the mapping. Effect of better learning has also explored in both network by applying adaptivenesss in their transform function available in the active nodes. Single image based training has given for few number of iterations in the development of mapping process. It is observed that proposed method has self adjusted content aware oriented edge detection where as many existing methods like Sobel, Prewitt have shown their limitations in observing the edges associated with contents having similar shade in the surroundings.

Experimental validation of image contrast correlation between ultra-small-angle X-ray scattering and grating-based dark-field imaging using a laser-driven compact X-ray source

X-ray phase and dark-field contrast have recently been the source of much attention in the field of X-ray imaging, as they both contribute new imaging signals based on physical principles that differ from conventional X-ray imaging. With a so-called Talbot grating interferometer, both phase-contrast and dark-field images are obtained simultaneously with the conventional attenuation-based X-ray image, providing three complementary image modalities that are intrinsically registered. Whereas the physical contrast mechanisms behind attenuation and phase contrast are well understood, a formalism to describe the dark-field signal is still in progress. In this article, we report on correlative experimental results obtained with a grating interferometer and with small-angle X-ray scattering. Furthermore, we use a proposed model to quantitatively describe the results, which could be of great importance for future clinical and biomedical applications of grating-based X-ray imaging.