Detección automática con snakes y representación 3D sobre imágenes cerebrales

Comunicación presentada en la VI Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA'95), Alicante, 15-17 noviembre 1995.

Recolonization of mortars by endolithic organisms on the walls of San Roque church in Campeche (Mexico): A case of tertiary bioreceptivity

San Roque church (Campeche, Mexico) was built at the end of the 17th century with a micritic limestone and lime mortar in baroque style. In 2005 the church exhibited heavy biodeterioration associated with the development of extensive dark green phototrophic-based biofilms. Several cyanobacteria belonging to the order Chroococcales and lichenized fungi (Toninia nordlandica, Lobaria quercizans, Lecanora subcarnea, Cystocoleus ebeneus) were predominant in the dark biofilm samples, as revealed by DNA-based molecular techniques. In 2009, a cleaning and restoration intervention was adopted; however, after few months, microbial recolonization started to be noticeable on the painted church walls, representing an early phototrophic-based recolonization. According to molecular analysis, scanning electron microscopy observations and digital image analysis of cross sections, new phototrophic-based colonization, composed of cyanobacteria and bryophytes, developed mainly beneath the restored mortars. The intrinsic properties of the mortars, the tropical climate of Campeche and the absence of a biocide treatment in the restoration protocol influenced the recolonization of the church façades and enhanced the overall rate of deterioration in a short-term period.

Changes in the Photoreceptor Mosaic of P23H-1 Rats During Retinal Degeneration: Implications for Rod-Cone Dependent Survival

Purpose. To investigate the spatiotemporal relationship between rod and cone degeneration in the P23H-1 rat. Methods. Control Sprague-Dawley (SD) and P23H-1 rats of ages ranging from P30 to P365 were used. Retinas were processed for whole mounts or cross sections and rods and cones were immunodetected. We used newly developed image analysis techniques to quantify the total population of L/M cones (the most abundant cones in the rat) and analyzed the rings of rod-cone degeneration. Results. In P23H-1 rats, rod degeneration occurs rapidly: first the rod outer segment shortens, at P30 there is extensive rod loss, and by P180 rod loss is almost complete except for the most peripheral retina. The numbers of L/M cones are, at all postnatal ages, lower in P23H-1 rats than in control SD rats, and decrease significantly with age (by P180). Rod and cone degeneration is spatiotemporally related and occurs in rings that appear already at P90 and spread throughout the entire retina. At P180, the rings of rod-cone degeneration are more abundant in the equatorial retina and are larger in the dorsal retina. Conclusions. This work describes for the first time that in the P23H-1 rat, rod and cone degeneration is spatiotemporally related and occurs in rings. Cone loss follows rod loss and starts very soon, even before P30, the first age analyzed here. The characteristics of the rings suggest that secondary cone degeneration is influenced by retinal position and/or other intrinsic or extrinsic factors.

Automatic Abdominal Aortic Aneurysm segmentation in MR images

Abdominal Aortic Aneurism is a disease related to a weakening in the aortic wall that can cause a break in the aorta and the death. The detection of an unusual dilatation of a section of the aorta is an indicative of this disease. However, it is difficult to diagnose because it is necessary image diagnosis using computed tomography or magnetic resonance. An automatic diagnosis system would allow to analyze abdominal magnetic resonance images and to warn doctors if any anomaly is detected. We focus our research in magnetic resonance images because of the absence of ionizing radiation. Although there are proposals to identify this disease in magnetic resonance images, they need an intervention from clinicians to be precise and some of them are computationally hard. In this paper we develop a novel approach to analyze magnetic resonance abdominal images and detect the lumen and the aortic wall. The method combines different algorithms in two stages to improve the detection and the segmentation so it can be applied to similar problems with other type of images or structures. In a first stage, we use a spatial fuzzy C-means algorithm with morphological image analysis to detect and segment the lumen; and subsequently, in a second stage, we apply a graph cut algorithm to segment the aortic wall. The obtained results in the analyzed images are pretty successful obtaining an average of 79% of overlapping between the automatic segmentation provided by our method and the aortic wall identified by a medical specialist. The main impact of the proposed method is that it works in a completely automatic way with a low computational cost, which is of great significance for any expert and intelligent system.