Radial Distortion Self-Calibration

In cameras with radial distortion, straight lines in space are in general mapped to curves in the image. Although epipolar geometry also gets distorted, there is a set of special epipolar lines that remain straight, namely those that go through the distortion center. By finding these straight epipolar lines in camera pairs we can obtain constraints on the distortion center(s) without any calibration object or plumbline assumptions in the scene. Although this holds for all radial distortion models we conceptually prove this idea using the division distortion model and the radial fundamental matrix which allow for a very simple closed form solution of the distortion center from two views (same distortion) or three views (different distortions). The non-iterative nature of our approach makes it immune to local minima and allows finding the distortion center also for cropped images or those where no good prior exists. Besides this, we give comprehensive relations between different undistortion models and discuss advantages and drawbacks.

Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention

Loneliness in Middle and Old Age

Purpose of the research: (a) To identify the degree of much loneliness reported in the Portuguese population over 50 years of age and (b) test whether loneliness can be predicted by socio-demographic, health related or social characteristic of the sample other than age. Materials and methods: 1174 late middle age and older adults were interviewed face to face by different interviewers across the country; after the informed consent was signed, we asked the participants several socio-demographic and health-related questions; finally we asked ‘‘How often do you feel lonely?’’ and participants responded according to a five point Likert scale. Principal results: The results showed that 12% of participants reporting feeling lonely often or always, whereas 40% reporting never feeling lonely. The remaining 48% self-reported they felt lonely seldom or sometimes. Additionally, results show that, when taken together, variables such as marital status, type of housing, residence settings, health conditions, social satisfaction, social isolation, lack of interest, transportation, and age were predictors of loneliness. Major conclusions: (1) The association of loneliness with advanced age has been greatly exaggerated by mass media and common sense; (2) But although our findings did not confirm the most alarmist views, the 12% of older adults reporting that they are feeling lonely always or often should be cause for attention and concern. It is necessary to understand the meaning, reasons and level of suffering implied on those feelings of loneliness. (3) Our findings suggest that it makes no sense to construe age as a singular feature or cause for feelings of loneliness. Instead, age and also a number of other features combine to predict feelings of loneliness. But even with our predictor variables there was a substantial of variance left unexplained. Therefore it is necessary to continue exploring how feelings of loneliness arise from the experience of living and how they can be changed.