The development of software for automatic contouring of the left ventricle on echographic video sequence

В статье описан полуавтоматический алгоритм оконтуривания левого желудочка сердца на эхографических видеопоследовательностях. Произведена качественная оценка результатов построения контура для 14 пациентов. Разработана программа, которая позволяет врачам кардиологам строить контуры в полуавтоматическом режиме и оценивать качество построенных контуров. Данный алгоритм может быть применим для решения поставленной задачи.This article describes a semi-automatic algorithm of delineation of the left ventricle of the heart on the echographic video sequences. A qualitative assessment of the results of the contour construction was made for 14 patients. A program that allows to cardiologists to build contour in semi-automatic mode, and assess the quality of contouring This algorithm can be applied to solve the problem

ВІДСЛІДКОВУВАННЯ РУХОМИХ ОБ’ЄКТІВ У ВІДЕОПОТОКАХ РЕАЛЬНОГО ЧАСУ

This article describes a new method for tracking moving objects in the field of multiple cameras. The main feature of the proposed method is the ability to work in real time by significantly reducing procedural complexity. Based on this method, authors developed system to identify and support transport traffic. The results of practical experiments on the system show high accuracy of identification of moving objects, building the exact trajectory of their movement and possibility of them accompanied. Numerous practical experiments confirmed the efficiency of the proposed method in video surveillance systems with up to 8 cameras.Описано новий метод відслідковування рухомих об’єктів в полі зору декількох камер відеоспостереження. Основною особливістю розробленого методу є можливість роботи в режимі реального часу завдяки значному зменшенню процедурної складності. На основі розробленого методу створено систему багатокамерної ідентифікації та супроводу руху транспортних засобів. Результати практичних експериментів щодо роботи системи показують високу точність ідентифікації рухомих об’єктів, побудову точної траєкторії їх руху та можливість їх супроводу. Численні практичні експерименти підтвердили ефективність використання розробленого методу у системах відеоспостереження, що містять до 8 камер

Computer Vision Based Object Tracking as a Teaching Aid for High School Physics Experiments

Experiments play a vital role in science education. In high school physics, especially in mechanics, many experiments are conducted where tracking a single or multiple objects are required. In most situations students visually observe the motion of objects and take the measurements. This manual method is time consuming, generates higher error and incapable of producing multiple readings rapidly. The research described in this work introduces a simple mechanism to integrate computer vision based tracking to enhance the quality of measurements and to new ways of looking at experiments. The case study consists of three standard experiments. In the first experiment a motion of the simple pendulum was tracked. Using computer vision students were able to obtain a correlation of 0.99 between the calculated period and the theoretical period. In addition, it was possible to calculate the position and the velocity of the bob more than 30 times during a single oscillation. Students were able to plot the extra data points for a better understanding of the simple harmonic motion, which was not possible in the manual method. Second experiment was focused on measuring the terminal velocity of a ball moving through a viscous medium. Final case study was on tracking multiple particles in a moving fluid. In all three experiments computer vision based system provided more accurate and higher number of data points than the manual method. This helps students to understanding the underline theory better. The tracking system was consisted of a digital camera, image preprocessing sub system, feature extraction subsystem, object identification subsystem and data export subsystem. The system was successfully tested on a normal PC which is cost effective to be used in high schools. Based on the case studies it was concluded that such systems can be used in high schools to improve the quality of experiments conducted.

Positive Feedback Between PU.1 and the Cell Cycle Controls Myeloid Differentiation

Regulatory gene circuits with positive-feedback loops control stem cell differentiation, but several mechanisms can contribute to positive feedback. Here, we dissect feedback mechanisms through which the transcription factor PU.1 controls lymphoid and myeloid differentiation. Quantitative live-cell imaging revealed that developing B cells decrease PU.1 levels by reducing PU.1 transcription, whereas developing macrophages increase PU.1 levels by lengthening their cell cycles, which causes stable PU.1 accumulation. Exogenous PU.1 expression in progenitors increases endogenous PU.1 levels by inducing cell cycle lengthening, implying positive feedback between a regulatory factor and the cell cycle. Mathematical modeling showed that this cell cycle–coupled feedback architecture effectively stabilizes a slow-dividing differentiated state. These results show that cell cycle duration functions as an integral part of a positive autoregulatory circuit to control cell fate

Adaptive Shape Kernel-Based Mean Shift Tracker in Robot Vision System

This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as the tracking video. The proposed kernel searches the shape in the low-dimensional shape space obtained by nonlinear manifold learning technique and constructs the adaptive kernel shape in the high-dimensional shape space. It can improve mean shift tracker performance to track object position and object contour and avoid the background clutter. In the experimental part, we take the walking human as example to validate that our method is accurate and robust to track human position and describe human contour

Redes Neuronales : Aplicaciones

Esta línea de investigación se centra en el estudio y desarrollo de diferentes estrategias de adaptación de Redes Neuronales basadas tanto en técnicas de entrenamiento como en procesos evolutivos que permitan optimizar las soluciones obtenidas. Interesa especialmente la transferencia de tecnología a las áreas de la minería de datos y la robótica. Con respecto a la primera, se estudian diferentes metodologías aplicadas al reconocimiento adaptativo de patrones a fin de obtener caracterizaciones que ayuden a la toma de decisiones. En el área de la robótica, el énfasis está puesto en el estudio, investigación y desarrollo de aplicaciones de tiempo real basadas en redes neuronales evolutivas, especialmente aplicadas a situaciones cuya solución requiere del aprendizaje de estrategias. Se trabaja en el desarrollo de nuevos métodos para la resolución de problemas utilizando agentes capaces de percibir y actuar en entornos complejos cuyos resultados son aplicados directamente en esta área.Eje: Sistemas de información y MetaheurísticaRed de Universidades con Carreras en Informática (RedUNCI