Unsupervised active regions for multiresolution image segmentation

An unsupervised approach to image segmentation which fuses region and boundary information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: the guidance of seed placement, the control of decision criterion, and the boundary refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method

Further insights in trichothiodistrophy: a clinical, microscopic, and ultrastructural study of 20 cases and literature review

Background: Trichothiodistrophy (TTD) is a rare autosomal recessive condition that is characterized by a specific congenital hair shaft dysplasia caused by deficiency of sulfur associated with a wide spectrum of multisystem abnormalities. In this article, we study clinical, microscopic, and ultrastructural findings of 20 patients with TTD with the aim to add further insights regarding to this rare condition. Additionally, analyses of our results are compared with those extracted from the literature in order to enhance its comprehensibility. Materials and Methods: Twenty cases of TTD were included: 7 from Mexico and 14 from Spain. Clinical, microscopic, scanning electron microscopy (SEM) studies and X-ray microanalysis (XrMa) were carried out in all of them. Genetic studies were performed in all seven Mexican cases. Patients with xeroderma pigmentosum and xeroderma pigmentosum/TTD-complex were excluded. Results: Cuticular changes and longitudinal crests of the hair shaft were demonstrated. These crests were irregular, disorganized, following the hair longest axis. Hair shaft sulfur deficiency was disposed discontinuously and intermittently rather than uniformly. This severe decrease of sulfur contents was located close to the trichoschisis areas. Only five patients did not show related disturbances. Micro-dolichocephaly was observed in five cases and represented the most frequent facial dysmorphism found. It is also remarkable that all patients with urologic malformations also combined diverse neurologic disorders. Moreover, three Mexican sisters demonstrated the coexistence of scarce pubic vellus hair, developmental delay, onychodystrophy, and maxillar/mandibullar hypoplasia. Conclusions: TTD phenotype has greatly varied from very subtle forms to severe alterations such as neurologic abnormalities, blindness, lamellar ichthyosis and gonadal malformations. Herein, a multisystem study should be performed mandatorily in patients diagnosed with TTD.

Further insights in trichothiodistrophy: a clinical, microscopic, and ultrastructural study of 20 cases and literature review

Background: Trichothiodistrophy (TTD) is a rare autosomal recessive condition that is characterized by a specific congenital hair shaft dysplasia caused by deficiency of sulfur associated with a wide spectrum of multisystem abnormalities. In this article, we study clinical, microscopic, and ultrastructural findings of 20 patients with TTD with the aim to add further insights regarding to this rare condition. Additionally, analyses of our results are compared with those extracted from the literature in order to enhance its comprehensibility. Materials and Methods: Twenty cases of TTD were included: 7 from Mexico and 14 from Spain. Clinical, microscopic, scanning electron microscopy (SEM) studies and X-ray microanalysis (XrMa) were carried out in all of them. Genetic studies were performed in all seven Mexican cases. Patients with xeroderma pigmentosum and xeroderma pigmentosum/TTD-complex were excluded. Results: Cuticular changes and longitudinal crests of the hair shaft were demonstrated. These crests were irregular, disorganized, following the hair longest axis. Hair shaft sulfur deficiency was disposed discontinuously and intermittently rather than uniformly. This severe decrease of sulfur contents was located close to the trichoschisis areas. Only five patients did not show related disturbances. Micro-dolichocephaly was observed in five cases and represented the most frequent facial dysmorphism found. It is also remarkable that all patients with urologic malformations also combined diverse neurologic disorders. Moreover, three Mexican sisters demonstrated the coexistence of scarce pubic vellus hair, developmental delay, onychodystrophy, and maxillar/mandibullar hypoplasia. Conclusions: TTD phenotype has greatly varied from very subtle forms to severe alterations such as neurologic abnormalities, blindness, lamellar ichthyosis and gonadal malformations. Herein, a multisystem study should be performed mandatorily in patients diagnosed with TTD.

Image Segmentation Using Information Bottleneck Method

In image processing, segmentation algorithms constitute one of the main focuses of research. In this paper, new image segmentation algorithms based on a hard version of the information bottleneck method are presented. The objective of this method is to extract a compact representation of a variable, considered the input, with minimal loss of mutual information with respect to another variable, considered the output. First, we introduce a split-and-merge algorithm based on the definition of an information channel between a set of regions (input) of the image and the intensity histogram bins (output). From this channel, the maximization of the mutual information gain is used to optimize the image partitioning. Then, the merging process of the regions obtained in the previous phase is carried out by minimizing the loss of mutual information. From the inversion of the above channel, we also present a new histogram clustering algorithm based on the minimization of the mutual information loss, where now the input variable represents the histogram bins and the output is given by the set of regions obtained from the above split-and-merge algorithm. Finally, we introduce two new clustering algorithms which show how the information bottleneck method can be applied to the registration channel obtained when two multimodal images are correctly aligned. Different experiments on 2-D and 3-D images show the behavior of the proposed algorithms

Efficient image mosaicing for multi-robot visual underwater mapping

Robotic platforms have advanced greatly in terms of their remote sensing capabilities, including obtaining optical information using cameras. Alongside these advances, visual mapping has become a very active research area, which facilitates the mapping of areas inaccessible to humans. This requires the efficient processing of data to increase the final mosaic quality and computational efficiency. In this paper, we propose an efficient image mosaicing algorithm for large area visual mapping in underwater environments using multiple underwater robots. Our method identifies overlapping image pairs in the trajectories carried out by the different robots during the topology estimation process, being this a cornerstone for efficiently mapping large areas of the seafloor. We present comparative results based on challenging real underwater datasets, which simulated multi-robot mapping

Improving the oscillating grid method to characterize aquaculture biosolids using a laser beam and image analysis

Quickremovalofbiosolidsinaquaculturefacilities,andspeciallyinrecirculatingaquaculturesystems(RAS),isoneofthemostimportantstepinwastemanagement.Sedimentationdynamicsofbiosolidsinanaquaculturetankwilldeterminetheiraccumulationatthebottomofthetank.