Waldemar Wójcik

Assessment of significance of features acquired from thyroid ultrasonograms in Hashimoto's disease

IntroductionThis paper concerns the analysis of the features obtained from thyroid ultrasound images in left and right transverse and longitudinal sections. In the image analysis, the thyroid lobe is treated as a texture for healthy subjects and patients with Hashimoto’s disease. The applied methods of analysis and image processing were profiled to obtain 10 features of the image. Then, their significance in the classification was shown.MaterialIn this study, the examined group consisted of 29 healthy subjects aged 18 to 60 and 65 patients with Hashimotos disease. For each subject, four ultrasound images were taken. They were all in transverse and longitudinal sections of the right and left lobe of the thyroid, which gave 376 images in total.Method10 different features obtained from each ultrasound image were suggested. The analyzed thyroid lobe was marked automatically or manually with a rectangular element.ResultsThe analysis of 10 features and the creation for each one of them their own decision tree configuration resulted in distinguishing 3 most significant features. The results of the quality of classification show accuracy above 94% for a non-trimmed decision tree.

The use of decision tree induction and artificial neural networks for automatic diagnosis of Hashimoto's disease

Methods for classification of ultrasound thyroid images have been presented. These methods allow us to classify examined patients as either sick or healthy. Decision tree induction and a multilayer perceptron neural network have been used to build classification models. Test results showed that the proposed methods can provide a starting point for building a support system in the process of medical diagnosis. Better accuracy of classifiers was achieved for the normalized images. We have also found that, under adopted assumptions, the results obtained for them were statistically significant in contrast to original images. The proposed methods allow us to separate a fairly large group of incorrectly classified cases. According to the authors, this group may contain features of the early stage of Hashimotos disease.

ECTL application for carbon monoxide measurements

Semiconductor lasers, which can be surely characterize by many of their advantages, have been used for measurements of concentration of gases for many years. Doing measurements in industrial conditions, because of its several difficulties, needs using special technology of measurements. In this article using modified, correlated absorption spectroscopy, in order to measure CO concentration, has been shown.

Influence of the measurement method of features in ultrasound images of the thyroid in the diagnosis of Hashimoto’s disease

IntroductionThis paper shows the influence of a measurement method of features in the diagnosis of Hashimoto’s disease. Sensitivity of the algorithm to changes in the parameters of the ROI, namely shift, resizing and rotation, has been presented. The obtained results were also compared to the methods known from the literature in which decision trees or average gray level thresholding are used.MaterialIn the study, 288 images obtained from patients with Hashimoto’s disease and 236 images from healthy subjects have been analyzed. For each person, an ultrasound examination of the left and right thyroid lobe in transverse and longitudinal sections has been performed.MethodWith the use of the developed algorithm, a discriminant analysis has been conducted for the following five options: linear, diaglinear, quadratic, diagquadratic and mahalanobis. The left and right thyroid lobes have been analyzed both together and separately in transverse and longitudinal sections. In addition, the algorithm enabled to analyze specificity and sensitivity as well as the impact of sensitivity of ROI shift, repositioning and rotation on the measured features.Results and summaryThe analysis has shown that the highest accuracy was obtained for the longitudinal section (LD) with the method of linear, yielding sensitivity = 76%, specificity = 95% and accuracy ACC = 84%. The conducted sensitivity assessment confirms that changes in the position and size of the ROI have little effect on sensitivity and specificity. The analysis of all cases, that is, images of the left and right thyroid lobes in transverse and longitudinal sections, has shown specificity ranging from 60% to 95% and sensitivity from 62% to 89%. Additionally, it was shown that the value of ACC for the method using decision trees as a classifier is equal to 84% for the analyzed data. Thresholding of average brightness of the ROI gave ACC equal to 76%.

Optical fiber system for combustion quality analysis in power boilers

The introduction of low emission techniques of combustion caused side-effects like oxygen lean corrosion. It also enforced more precise management of technological air, better coal milling and application of devices for combustion process monitoring. In the article authors presented their own solution of optical fiber system for combustion quality evaluation, already operating on power boiler type OP-650. Its functionality was described together with selected results of measurements. Directions of further development of the system were also indicated.

Optical fiber technology development in Poland

Optical fiber technology is an important branch of science and technology, but also economy. Together with related disciplines it creates wider areas like optoelectronics and photonics. Optical fiber technology is developed in this country rather dynamically, proportionally to the available funds designed locally for research and applications. Recently this development was enhanced with considerable funds from European Operational Funds Innovative Economy POIG and Human Capital POKL. The paper summarizes the development of optical fiber technology in Poland from academic perspective during the period of last 2-3 years. The digest is very probably not full. An emphasis is put on development of optical fiber manufacturing methods. This development was illustrated by a few examples of optical fiber applications.

Combustion diagnosis by image processing

The paper presents the way that colour can serve solving the problem of calibration points indexing in a camera geometrical calibration process. We propose a technique in which indexes of calibration points in a black-and-white chessboard are represented as sets of colour regions in the neighbourhood of calibration points. We provide some general rules for designing a colour calibration chessboard and provide a method of calibration image analysis. We show that this approach leads to obtaining better results than in the case of widely used methods employing information about already indexed points to compute indexes. We also report constraints concerning the technique. Nowadays we are witnessing an increasing need for camera geometrical calibration systems. They are vital for such applications as 3D modelling, 3D reconstruction, assembly control systems, etc. Wherever possible, calibration objects placed in the scene are used in a camera geometrical calibration process. This approach significantly increases accuracy of calibration results and makes the calibration data extraction process easier and universal. There are many geometrical camera calibration techniques for a known calibration scene [1]. A great number of them use as an input calibration points which are localised and indexed in the scene. In this paper we propose the technique of calibration points indexing which uses a colour chessboard. The presented technique was developed by solving problems we encountered during experiments with our earlier methods of camera calibration scene analysis [2]-[3]. In particular, the proposed technique increases the number of indexed points points in case of local lack of calibration points detection. At the beginning of the paper we present a way of designing a chessboard pattern. Then we describe a calibration point indexing method, and finally we show experimental results. A black-and-white chessboard is widely used in order to obtain sub-pixel accuracy of calibration points localisation [1]. Calibration points are defined as corners of chessboard squares. Assuming the availability of rough localisation of these points, the points can be indexed. Noting that differences in distances between neighbouring points in calibration scene images differ slightly, one of the local searching methods can be employed (e.g. [2]). Methods of this type search for a calibration point to be indexed, using a window of a certain size. The position of the window is determined by a vector representing the distance between two previously indexed points in the same row or column. However, experiments show that this approach has its disadvantages, as described below. * E-mail: A.Nowakowski@ire.pw.edu.pl Firstly, there is a danger of omitting some points during indexing in case of local lack of calibration points detection in a neighbourhood (e.g. caused by the presence of non-homogeneous light in the calibration scene). A particularly unfavourable situation is when the local lack of detection effects in the appearance of separated regions of detected calibration points. It is worth saying that such situations are likely to happen for calibration points situated near image borders. Such points are very important for the analysis of optical nonlinearities, and a lack of them can significantly influence the accuracy of distortion modelling. Secondly, such methods may give wrong results in the case of optical distortion with strong nonlinearities when getting information about the neighbouring index is not an easy task. Beside this, the methods are very sensitive to a single false localisation of a calibration point. Such a single false localisation can even result in false indexing of a big set of calibration points. To avoid the above-mentioned problems, we propose using a black-and-white chessboard which contains the coded index of a calibration point in the form of colour squares situated in the nearest neighbourhood of each point. The index of a certain calibration point is determined by colours of four nearest neighbouring squares (Fig.1). An order of squares in such foursome is important. Because the size of a colour square is determined only by the possibility of correct colour detection, the size of a colour square can be smaller than the size of a black or white square. The larger size of a black or white square is determined by the requirements of the exact localisation step which follows the indexing of calibration points [3]. In this step, edge information is extracted from a blackand-white chessboard. This edge information needs larger Artur Nowakowski, Wladyslaw Skarbek Institute of Radioelectronics, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warszawa, A.Nowakowski@ire.pw.edu.pl Received February 10, 2009; accepted March 27, 2009; published March 31, 2009 http://www.photonics.pl/PLP

Controlling combustion process in power boiler by genetic algorithm and neural network

An analyse of evolutionary algorithm operation allows us to understand how controlled spontaneity of an individual specimen leads to dynamic order of the whole community that efficiently uses emerging adaptive possibilities. This paper presents sequel of research concerning implementation of GA in controlling burning process in industrial conditions. A simulation was conducted and proved that implementing GA to the process is possible and brings improvement of flue gases parameters, what is a direct measure of power boiler quality of work, both in ecologic and economical way.

Application of Selected Classification Methods for Detection of Hashimoto’s Thyroiditis on the Basis of Ultrasound Images

The article presents methods for classification of ultrasound thyroid images. These methods allow us to classify analyzed cases as sick or healthy. They allow us to separate a fairly large group of incorrectly classified cases as well. According to the authors, this group may contain features of the early stage of Hashimoto’s disease. Decision tree induction and artificial neural networks have been used to build classification models. Test results showed that the proposed methods can provide a starting point to build a support system in the process of medical diagnosis.

Application of flame monitoring system for flame spectrum analysis in industrial conditions

The flame monitoring system is intended to use in industrial condition for controlling pulverized coal combustion in power boiler. Placing the fiber-optic probes close to the each burner, one can obtain detailed information of the coal combustion process within the single burner. In order to enhance flame-monitoring system sensitivity for detection of fuels composition changes, we have measured flame emission spectra.