Chest CT at a dose below 0.3 mSv : impact of iterative reconstruction on image quality and lung analysis

Le nombre d'examens tomodensitométriques (Computed Tomography, CT) effectués chaque année étant en constante augmentation, différentes techniques d'optimisation, dont les algorithmes de reconstruction itérative permettant de réduire le bruit tout en maintenant la résolution spatiale, ont étés développées afin de réduire les doses délivrées. Le but de cette étude était d'évaluer l'impact des algorithmes de reconstruction itérative sur la qualité image à des doses effectives inférieures à 0.3 mSv, comparables à celle d'une radiographie thoracique. Vingt CT thoraciques effectués à cette dose effective ont été reconstruits en variant trois paramètres: l'algorithme de reconstruction, rétroprojection filtrée versus reconstruction itérative iDose4; la matrice, 5122 versus 7682; et le filtre de résolution en densité (mou) versus spatiale (dur). Ainsi, 8 séries ont été reconstruites pour chacun des 20 CT thoraciques. La qualité d'image de ces 8 séries a d'abord été évaluée qualitativement par deux radiologues expérimentés en aveugle en se basant sur la netteté des parois bronchiques et de l'interface entre le parenchyme pulmonaire et les vaisseaux, puis quantitativement en utilisant une formule de merit, fréquemment utilisée dans le développement de nouveaux algorithmes et filtres de reconstruction. La performance diagnostique de la meilleure série acquise à une dose effective inférieure à 0.3 mSv a été comparée à celle d'un CT de référence effectué à doses standards en relevant les anomalies du parenchyme pulmonaire. Les résultats montrent que la meilleure qualité d'image, tant qualitativement que quantitativement a été obtenue en utilisant iDose4, la matrice 5122 et le filtre mou, avec une concordance parfaite entre les classements quantitatif et qualitatif des 8 séries. D'autre part, la détection des nodules pulmonaires de plus de 4mm étaient similaire sur la meilleure série acquise à une dose effective inférieure à 0.3 mSv et le CT de référence. En conclusion, les CT thoraciques effectués à une dose effective inférieure à 0.3 mSv reconstruits avec iDose4, la matrice 5122 et le filtre mou peuvent être utilisés avec confiance pour diagnostiquer les nodules pulmonaires de plus de 4mm.

Mobile Subscription Acquisition and Retention Costs - An Actvity-Based Model

The objective of this master’s thesis was to develop a model for mobile subscription acquisition cost, SAC, and mobile subscription retention cost, SRC, by applying activity-based cost accounting principles. The thesis was conducted as a case study for a telecommunication company operating on the Finnish telecommunication market. In addition to activity-based cost accounting there were other theories studied and applied in order to establish a theory framework for this thesis. The concepts of acquisition and retention were explored in a broader context with the concepts of customer satisfaction, loyalty and profitability and eventually customer relationship management to understand the background and meaning of the theme of this thesis. The utilization of SAC and SRC information is discussed through the theories of decision making and activity-based management. Also, the present state and future needs of SAC and SRC information usage at the case company as well as the functions of the company were examined by interviewing some members of the company personnel. With the help of these theories and methods it was aimed at finding out both the theory-based and practical factors which affect the structure of the model. During the thesis study it was confirmed that the existing SAC and SRC model of the case company should be used as the basis in developing the activity-based model. As a result the indirect costs of the old model were transformed into activities and the direct costs were continued to be allocated directly to acquisition of new subscriptions and retention of old subscriptions. The refined model will enable managing the subscription acquisition, retention and the related costs better through the activity information. During the interviews it was found out that the SAC and SRC information is also used in performance measurement and operational and strategic planning. SAC and SRC are not fully absorbed costs and it was concluded that the model serves best as a source of indicative cost information. This thesis does not include calculating costs. Instead, the refined model together with both the theory-based and interview findings concerning the utilization of the information produced by the model will serve as a framework for the possible future development aiming at completing the model.

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.

Local Embeddedness and Knowledge Acquisition and How They Affect Finnish Business Operations in Russia

This pilot project aims examine the factors of the Finnish subsidiaries local embeddedness, their knowledge creation capabilities and the transfer mechanisms of new practices in the context of the Russian market. The research is designed as a multiple case study conducted with a qualitative approach. The empirical data consists of the interviews of the four Finnish case companies operating in the Kaluga region and three local partner companies. The deductive and inductive approaches were employed to conduct the analysis of the data. The propositions for the future study were developed in the conclusive chapters of the research, where we propose that the factor of the economy growth and industrialization matters in terms of subsidiaries’ role dedication, their knowledge creation capabilities, and direction of the knowledge flow within the local environment.

Image analysis and definition of nuclear phenotypes

Some basic topics concerned with the extraction of textural and geometric information from cell nucleus images as well as description and characterization of chromatin supraorganization and consequent classification of nuclear phenotypes are presented.

Acquisition and transfer of experiential learning from rock climbing to the corporate workplace

There were three purposes to this study. The first purpose was to determine how learning can be influenced by various factors i~ the rock climbing experience. The second purpose was to examine what people can learn from the rock climbing experience. The third purpose was to investigate whether that learning can transfer from the rock climbing experience to the subjects' real life in the workplace. Ninety employees from a financial corporation in the Niagara Region volunteered for this study. All subjects were surveyed throughout a one-day treatment. Ten were purposefully selected one month later for interviews. Ten themes emerged from the subjects in terms of what was learned. Inspiration, motivation, and determination, preparation, goals and limitations, perceptions and expectations, confidence and risk taking, trust and support, teamwork, feedback and encouragement, learning from failure, and finally, skills and flow. All participants were able to transfer what was learned back to the workplace. The results of this study suggested that subjects' learning was influenced by their ability to: take risks in a safe environment, fail without penalty, support each other, plan without time constraints, and enjoy the company of fellow workers that they wouldn't normally associate with. Future directions for research should include different types of treatments such as white water rafting, sky diving, tall ship sailing, or caving.

A Foucauldian Analysis of Power and Representation in an Attempt to Run a Photovoice Project with Youth

This project evolved out of a search for ways to conduct research on “others” in a way that does not exploit, stigmatize or misrepresent their experience. This thesis is an ethnographic study in leisure research and youth work and an experiment in running a photovoice project. Photovoice is a participatory visual method that embodies the emancipatory ideal of empowering others through self-representation. The literature on photovoice lacks a comprehensive discussion on the complexity of power and representation. Postmodern theorists have proposed that participatory methods are not benign and that initiatives are acts of power in themselves that produce effects (Cook & Kothari, 2001). A Foucauldian analysis of power is used to deconstruct the researcher’s practice and reflect on why and how youth are “engaged”. This project seeks to embrace the principle of working “with” others, but also work from a postmodern perspective that acknowledges power and representation as ongoing problems.

Multichannel Remote Data Acquisition and Analysing Systems For Fisheries / Environmental Investigations

Remote Data acquisition and analysing systems developed for fisheries and related environmental studies have been reported. It consists of three units. The first one namely multichannel remote data acquisition system is installed at the remote place powered by a rechargeable battery. It acquires and stores the 16 channel environmental data on a battery backed up RAM. The second unit called the Field data analyser is used for insitue display and analysis of the data stored in the backed up RAM. The third unit namely Laboratory data analyser is an IBM compatible PC based unit for detailed analysis and interpretation of the data after bringing the RAM unit to the laboratory. The data collected using the system has been analysed and presented in the form of a graph. The system timer operated at negligibly low current, switches on the power to the entire remote operated system at prefixed time interval of 2 hours.Data storage at remote site on low power battery backedupRAM and retrieval and analysis of data using PC are the special i ty of the system. The remote operated system takes about 7 seconds including the 5 second stabilization time to acquire and store data and is very ideal for remote operation on rechargeable bat tery. The system can store 16 channel data scanned at 2 hour interval for 10 days on 2K backed up RAM with memory expansion facility for 8K RAM.

Document Image Segmentation and Compression using Artificial Neural Networks and Evolutionary Methods

The work is intended to study the following important aspects of document image processing and develop new methods. (1) Segmentation ofdocument images using adaptive interval valued neuro-fuzzy method. (2) Improving the segmentation procedure using Simulated Annealing technique. (3) Development of optimized compression algorithms using Genetic Algorithm and parallel Genetic Algorithm (4) Feature extraction of document images (5) Development of IV fuzzy rules. This work also helps for feature extraction and foreground and background identification. The proposed work incorporates Evolutionary and hybrid methods for segmentation and compression of document images. A study of different neural networks used in image processing, the study of developments in the area of fuzzy logic etc is carried out in this work

Example Based Image Analysis and Synthesis

Image analysis and graphics synthesis can be achieved with learning techniques using directly image examples without physically-based, 3D models. In our technique: -- the mapping from novel images to a vector of "pose" and "expression" parameters can be learned from a small set of example images using a function approximation technique that we call an analysis network; -- the inverse mapping from input "pose" and "expression" parameters to output images can be synthesized from a small set of example images and used to produce new images using a similar synthesis network. The techniques described here have several applications in computer graphics, special effects, interactive multimedia and very low bandwidth teleconferencing.

The importance of parental involvement in language acquisition and activities and techniques to enhance the home-school connection

This study discusses the importance of parental involvement in children’s language development, and the related project offers parents books and activities to assist them in developing their children’s linguistic skills.