Similarity Search in Medical Data

The ongoing automation in our modern information society leads to a tremendous rise in the amount as well as complexity of collected data. In medical imaging for example the electronic availability of extensive data collected as part of clinical trials provides a remarkable potentiality to detect new relevant features in complex diseases like brain tumors. Using data mining applications for the analysis of the data raises several problems. One problem is the localization of outstanding observations also called outliers in a data set. In this work a technique for parameter-free outlier detection, which is based on data compression and a general data model which combines the Generalized Normal Distribution (GND) with independent components, to cope with existing problems like parameter settings or implicit data distribution assumptions, is proposed. Another problem in many modern applications amongst others in medical imaging is the efficient similarity search in uncertain data. At present, an adequate therapy planning of newly detected brain tumors assumedly of glial origin needs invasive biopsy due to the fact that prognosis and treatment, both vary strongly for benign, low-grade, and high-grade tumors. To date differentiation of tumor grades is mainly based on the expertise of neuroradiologists examining contrast-enhanced Magnetic Resonance Images (MRI). To assist neuroradiologist experts during the differentiation between tumors of different malignancy we proposed a novel, efficient similarity search technique for uncertain data. The feature vector of an object is thereby not exactly known but is rather defined by a Probability Density Function (PDF) like a Gaussian Mixture Model (GMM). Previous work is limited to axis-parallel Gaussian distributions, hence, correlations between different features are not considered in these similarity searches. In this work a novel, efficient similarity search technique for general GMMs without independence assumption is presented. The actual components of a GMM are approximated in a conservative but tight way. The conservativity of the approach leads to a filter-refinement architecture, which guarantees no false dismissals and the tightness of the approximations causes good filter selectivity. An extensive experimental evaluation of the approach demonstrates a considerable speed-up of similarity queries on general GMMs. Additionally, promising results for advancing the differentiation between brain tumors of different grades could be obtained by applying the approach to four-dimensional Magnetic Resonance Images of glioma patients

Проект "Малая академия наук "Scientrium"" как пример организации исследовательской деятельности учащихся

Рассматривается исследовательская деятельность учащихся старших классов. Освещается реализация социально значимого проекта по вовлечению их в исследовательскую и околонаучную деятельность на базе Национального исследовательского Томского политехнического университета, Томской областной детской общественной организации «Хобби-центр» и Томского областного института повышения квалификации и переподготовки работников образования. Показан механизм формирования научных команд, позволяющий эффективно организовать исследовательскую работу учащихся старших классов под руководством сотрудников университета и студентов.The article discusses research activity of high schoolchild. Covers the implementation of socially significant project to engage them in research and allied activities in the framework of the National research Tomsk Polytechnic University, Tomsk regional children's public organization «Hobby-center» and the Tomsk regional Institute of advanced training and retraining of workers of education. The mechanism of formation of research teams to effectively organize the research work of senior students under the guidance of University staff and students

Судно с электроприводом от солнечной батареи

Объектом исследования является: Маломерное судно. Цель работы: Проект солнечной электростанции с накопителями электрической энергии, способной обеспечивать бесперебойное электроснабжение электромотора за счет преобразования энергии солнца. В процессе исследования проводились: расчет и выработки электрической энергии солнечными модулями, расчет и выбор емкости накопителей, разработка схемы солнечной электростанции, выбор оборудования солнечной электростанции, исследование динамических характеристик электропривода работающего от солнечной электростанции.The object of research is: a Small ship. The purpose of the research is to design a solar power plant with electric energy storage devices capable of providing uninterruptedly power supply to an electric motor by converting the solar energy. In the course of the research, the following activities were carried out: the calculation of electrical energy generation by solar modules, the calculation and selection of storage capacities, the development of a solar power plant scheme, selection of solar power plant equipment, study of the dynamic characteristics of an electric drive powered by a solar power plant

The quest for brain disorder biomarkers

The identification of disease markers in tissues and body fluids requires an extensive and thorough analysis of its protein constituents. In our efforts to identify biomarkers for affective and neurological disorders we are pursuing several different strategies. On one hand we are using animal models that represent defined phenotypes charactersistic for the respective disorder in humans. In addition, we are analyzing human specimens from carefully phenotyped patient groups. Several fractions representing different protein classes from human cerebrospinal fluid obtained by lumbar puncture are used for this purpose. Our biomarker identification efforts range from classical proteomics approaches such as two dimensional gel electrophoresis and mass spectrometry to phage display screens with cerebrospinal fluid antibodies

The quest for brain disorder biomarkers

The identification of disease markers in tissues and body fluids requires an extensive and thorough analysis of its protein constituents. In our efforts to identify biomarkers for affective and neurological disorders we are pursuing several different strategies. On one hand we are using animal models that represent defined phenotypes charactersistic for the respective disorder in humans. In addition, we are analyzing human specimens from carefully phenotyped patient groups. Several fractions representing different protein classes from human cerebrospinal fluid obtained by lumbar puncture are used for this purpose. Our biomarker identification efforts range from classical proteomics approaches such as two dimensional gel electrophoresis and mass spectrometry to phage display screens with cerebrospinal fluid antibodies