Effect on mood of subthalamic DBS for Parkinson's disease: a consecutive series of 24 patients

A series of 24 consecutive PD patients were prospectively studied prior to and within 6 months postoperatively for mood, motor, and cognitive status to investigate the effects on mood of subthalamic deep brain stimulation (DBS) in PD. In six patients (25%), mood state worsened significantly, and three were transiently suicidal despite clear motor improvement. Caregivers and patients should be educated about the potential impact of this neurosurgical procedure on mood.

Survey on image quality and dose levels used in Europe for mammography.

Quality assurance programmes are becoming a common practice in the field of mammography. At the present time several recommendations exist and different test objects are used to optimize this radiological procedure. The goal of this study was to check if geographically distant centres using different quality control procedures were comparable when using a common objective way of assessing image quality. The results show that consensus still needs to be found among radiologists to reach a satisfactory level of harmony between patient doses and image quality in Europe.

Comprehensive analysis of RET common and rare variant patientsin a series of Spanish Hirschsprung patients confirms a synergistic effect of both kinds of events

Background. RET is the major gene associated to Hirschsprung disease (HSCR) with differential contributions of its rare and common, coding and noncoding mutations to the multifactorial nature of this pathology. In the present study, we have performed a comprehensive study of our HSCR series evaluating the involvement of both RET rare variants (RVs) and common variants (CVs) in the context of the disease. Methods. RET mutational screening was performed by dHPLC and direct sequencing for the identification of RVs. In addition Taqman technology was applied for the genotyping of 3 RET CVs previously associated to HSCR, including a variant lying in an enhancer domain within RET intron 1 (rs2435357). Statistical analyses were performed using the SPSS v.17.0 to analyze the distribution of the variants. Results. Our results confirm the strongest association to HSCR for the "enhancer" variant, and demonstrate a significantly higher impact of it in male versus female patients. Integration of the RET RVs and CVs analysis showed that in 91.66% of cases with both kinds of mutational events, the enhancer allele is in trans with the allele bearing the RET RV. Conclusions. A gender effect exists on both the transmission and distribution of rare coding and common HSCR causing mutations. In addition, these RET CVs and RVs seem to act in a synergistic way leading to HSCR phenotype.

Time-series regression models to study the short-term effects of environmental factors on health

Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants

Infections after PRK could have a happy ending: a series of three cases.

BACKGROUND: Infectious keratitis after PRK remains a rare but potentially devastating complication. HISTORY AND SIGNS: Medical records of 3 male patients with infectious keratitis after uneventful PRK for myopia and astigmatism were reviewed retrospectively. PRK was performed using the Wavelight Allegretto excimer laser. Postoperative care included a bandage contact lens (BCL) for 5 days, topical antibiotics, ketorolac, and artificial tears. THERAPY AND OUTCOME: Keratitis presented 2 - 4 days postoperatively. In one case, each culture was negative (case 1), and was positive for Streptococcus pneumoniae (case 2) and Staphylococcus aureus (case 3). Final BSCVA (best spectacle corrected visual acuity) after intensive antibiotic treatment and removal of BCL were 1.0 (case 1), 0.9 (case 2) and 0.3 correctable to 0.8 with pinhole (case 3). CONCLUSIONS: Postoperative broad-spectrum antibiotics are mandatory after PRK to prevent infectious keratitis. However, resistant organisms are more and more common. The presence of a bandage soft contact lens after surgery is an unfavourable element that may increase risk of infection. Based on our case series, we suggest limiting soft contact lens wear during the two postoperative days even if the corneal ulceration is not healed.

Colour image processing

In the context of the round table the following topics related to image colour processing will be discussed: historical point of view. Studies of Aguilonius, Gerritsen, Newton and Maxwell. CIE standard (Commission International de lpsilaEclaraige). Colour models. RGB, HIS, etc. Colour segmentation based on HSI model. Industrial applications. Summary and discussion. At the end, video images showing the robustness of colour in front of B/W images will be presented

A method to obtain the integrated contour image in colour scenes

This paper describes a method to achieve the most relevant contours of an image. The presented method proposes to integrate the information of the local contours from chromatic components such as H, S and I, taking into account the criteria of coherence of the local contour orientation values obtained from each of these components. The process is based on parametrizing pixel by pixel the local contours (magnitude and orientation values) from the H, S and I images. This process is carried out individually for each chromatic component. If the criterion of dispersion of the obtained orientation values is high, this chromatic component will lose relevance. A final processing integrates the extracted contours of the three chromatic components, generating the so-called integrated contours image

Towards Detecting Changes in Underwater Image Sequences

Detecting changes between images of the same scene taken at different times is of great interest for monitoring and understanding the environment. It is widely used for on-land application but suffers from different constraints. Unfortunately, Change detection algorithms require highly accurate geometric and photometric registration. This requirement has precluded their use in underwater imagery in the past. In this paper, the change detection techniques available nowadays for on-land application were analyzed and a method to automatically detect the changes in sequences of underwater images is proposed. Target application scenarios are habitat restoration sites, or area monitoring after sudden impacts from hurricanes or ship groundings. The method is based on the creation of a 3D terrain model from one image sequence over an area of interest. This model allows for synthesizing textured views that correspond to the same viewpoints of a second image sequence. The generated views are photometrically matched and corrected against the corresponding frames from the second sequence. Standard change detection techniques are then applied to find areas of difference. Additionally, the paper shows that it is possible to detect false positives, resulting from non-rigid objects, by applying the same change detection method to the first sequence exclusively. The developed method was able to correctly find the changes between two challenging sequences of images from a coral reef taken one year apart and acquired with two different cameras

Estimating the motion of an underwater robot from a monocular image sequence

When underwater vehicles perform navigation close to the ocean floor, computer vision techniques can be applied to obtain quite accurate motion estimates. The most crucial step in the vision-based estimation of the vehicle motion consists on detecting matchings between image pairs. Here we propose the extensive use of texture analysis as a tool to ameliorate the correspondence problem in underwater images. Once a robust set of correspondences has been found, the three-dimensional motion of the vehicle can be computed with respect to the bed of the sea. Finally, motion estimates allow the construction of a map that could aid to the navigation of the robot

Surface registration from range image fusion

The registration of full 3-D models is an important task in computer vision. Range finders only reconstruct a partial view of the object. Many authors have proposed several techniques to register 3D surfaces from multiple views in which there are basically two aspects to consider. First, poor registration in which some sort of correspondences are established. Second, accurate registration in order to obtain a better solution. A survey of the most common techniques is presented and includes experimental results of some of them

Improving Clustering Algorithms for Image Segmentation using Contour and Region Information

In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach