Accurate detection of dysmorphic nuclei using dynamic programming and supervised classification

A vast array of pathologies is typified by the presence of nuclei with an abnormal morphology. Dysmorphic nuclear phenotypes feature dramatic size changes or foldings, but also entail much subtler deviations such as nuclear protrusions called blebs. Due to their unpredictable size, shape and intensity, dysmorphic nuclei are often not accurately detected in standard image analysis routines. To enable accurate detection of dysmorphic nuclei in confocal and widefield fluorescence microscopy images, we have developed an automated segmentation algorithm, called Blebbed Nuclei Detector (BleND), which relies on two-pass thresholding for initial nuclear contour detection, and an optimal path finding algorithm, based on dynamic programming, for refining these contours. Using a robust error metric, we show that our method matches manual segmentation in terms of precision and outperforms state-of-the-art nuclear segmentation methods. Its high performance allowed for building and integrating a robust classifier that recognizes dysmorphic nuclei with an accuracy above 95%. The combined segmentation-classification routine is bound to facilitate nucleus-based diagnostics and enable real-time recognition of dysmorphic nuclei in intelligent microscopy workflows

Off-line robot programming and graphical verification of path planning

The objective of this project was to develop or specify an integrated environment for off-line programming, graphical path verification, and debugging for robotic systems. Two alternatives were compared. The first was the integration of the ASEA Off-line Programming package with ROBSIM, a robotic simulation program. The second alternative was the purchase of the commercial product IGRIP. The needs of the RADL (Robotics Applications Development Laboratory) were explored and the alternatives were evaluated based on these needs. As a result, IGRIP was proposed as the best solution to the problem

Particle detection and tracking in fluorescence time-lapse imaging: a contrario approach

This paper proposes a probabilistic approach for the detection and the tracking of particles in fluorescent time-lapse imaging. In the presence of a very noised and poor-quality data, particles and trajectories can be characterized by an a contrario model, that estimates the probability of observing the structures of interest in random data. This approach, first introduced in the modeling of human visual perception and then successfully applied in many image processing tasks, leads to algorithms that neither require a previous learning stage, nor a tedious parameter tuning and are very robust to noise. Comparative evaluations against a well-established baseline show that the proposed approach outperforms the state of the art.Comment: Published in Journal of Machine Vision and Application

Developing serious games for cultural heritage: a state-of-the-art review

Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result, the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented

Locust-inspired vision system on chip architecture for collision detection in automotive applications

This paper describes a programmable digital computing architecture dedicated to process information in accordance to the organization and operating principles of the four-layer neuron structure encountered at the visual system of Locusts. This architecture takes advantage of the natural collision detection skills of locusts and is capable of processing images and ascertaining collision threats in real-time automotive scenarios. In addition to the Locust features, the architecture embeds a Topological Feature Estimator module to identify and classify objects in collision course.European Commission IST2001 - 38097Ministerio de Ciencia y Tecnología TIC2003 - 09817- C02 - 0

Dynamic spot analysis in the 2D electrophoresis gels images

Práce shrnuje faktory a parametry, které ovlivňují výsledky 2D elektroforézy, se zaměřením na zpracování obrazu jako jeden ze způsobů snížení nesprávné interpretace jejích výstupů. Proces zpracování obrazu využívá jako zdroj dat především obrazů z opakovaných provedení téhož pokusu, neboli víceplik. Pomocí analýzy obrazů víceplik je možno pozorovat nebo korigovat změny jednoho pokusu a také porovnávat je s výstupy jiných pokusů. Cílem práce je poskytnout podporu specialistovi, který má na starosti popsat vlastnosti struktur nacházejících se v elektroforetických obrazech.The text briefly describes factors and parameters which influence the results of 2D electrophoresis focusing on image processing as one manner to reduce incorrect interpretation of its outputs. As dataset, image processing performance uses images from repeated execution of one experiment also known as multiplicates. Using multiplicates analysis it is possible to observe or lower the changes of one experiment and to compare them with outputs of other experiments. The aim of this work is to provide support for specialist who takes care about describing the character patterns located in electrophoretic images.