<p><b>Objective:</b></p><p>To develop and validate computer-assisted morphometrical methods, based on stereological theory, in order to facilitate the analysis and quantitative measurements of biological tissue components.</p><p><b>Material and methods:</b></p><p>Biopsy specimens from the vaginal wall or from the vestibulum vaginae of healthy women, or from women suffering from incontinence or vestibulitis were used.</p><p>A number of histochemical methods for light microscopy were used, and modified for the different morphometrical analyses. Electron microscopy was used to reveal collagen fibre diameter.</p><p>Computer-assisted morphometry, based on image analysis and stereology, was employed to analyse the different tissue components in the biopsies. Computer programs for these purposes were developed and validated.</p><p><b>Results:</b></p><p>The results show that computer-assisted morphometry is of great value for quantitative measurements of the following tissue components:</p><p><b>Epithelium:</b> The epithelial structure, instead of just thickness, was measured in an unbiased way.</p><p><b>Collagen:</b> The collagen fibril diameter was determined in electron microscopic specimens, and the collagen content was analysed in light microscopic specimens.</p><p><b>Elastic fibres:</b> The amount of elastic fibres in the connective tissue was measured after visualisation by autofluorescence.</p><p><b>Vasculature:</b> A stereological method using a cycloid grid was implemented in a computer program. Healthy subjects were compared with patients suffering from vestibulitis. The results were identical in the two groups.</p><p><b>Smooth muscle:</b> A stereological method using a point grid was implemented in a computer program. Using the Delesse principle, the fibres were calculated as area fractions. The area fractions were highly variable among the different specimens.</p><p><b>Conclusion:</b></p><p>Morphometry, used correctly, is an important analysis method in histopathological research. It is important that the methods are as simple and user-friendly as possible. The present studies show that this methodology can be applied for most quantitative histological analyses.</p>

<b>Objective:</b> To develop and validate computer-assisted morphometrical methods, based on stereological theory, in order to facilitate the analysis and quantitative measurements of biological tissue components. <b>Material and methods:</b> Biopsy specimens from the vaginal wall or from the vestibulum vaginae of healthy women, or from women suffering from incontinence or vestibulitis were used. A number of histochemical methods for light microscopy were used, and modified for the different morphometrical analyses. Electron microscopy was used to reveal collagen fibre diameter. Computer-assisted morphometry, based on image analysis and stereology, was employed to analyse the different tissue components in the biopsies. Computer programs for these purposes were developed and validated. <b>Results:</b> The results show that computer-assisted morphometry is of great value for quantitative measurements of the following tissue components: <b>Epithelium:</b> The epithelial structure, instead of just thickness, was measured in an unbiased way. <b>Collagen:</b> The collagen fibril diameter was determined in electron microscopic specimens, and the collagen content was analysed in light microscopic specimens. <b>Elastic fibres:</b> The amount of elastic fibres in the connective tissue was measured after visualisation by autofluorescence. <b>Vasculature:</b> A stereological method using a cycloid grid was implemented in a computer program. Healthy subjects were compared with patients suffering from vestibulitis. The results were identical in the two groups. <b>Smooth muscle:</b> A stereological method using a point grid was implemented in a computer program. Using the Delesse principle, the fibres were calculated as area fractions. The area fractions were highly variable among the different specimens. <b>Conclusion:</b> Morphometry, used correctly, is an important analysis method in histopathological research. It is important that the methods are as simple and user-friendly as possible. The present studies show that this methodology can be applied for most quantitative histological analyses.

<p>Att applicera ansiktsigenkänning direkt på en mobiltelefon är en utmanande uppgift, inte minst med tanke på den begränsade minnes- och processorkapaciteten samt den stora variationen med avseende på ansiktsuttryck, hållning och ljusförhållande i inmatade bilder.</p><p>Det är fortfarande långt kvar till ett färdigutvecklat, robust och helautomatiskt ansiktsigenkänningssystem för den här miljön. Men resultaten i det här arbetet visar att genom att plocka ut feature-värden från lokala regioner samt applicera en välgjord warpstrategi för att minska problemen med variationer i position och rotation av huvudet, är det möjligt att uppnå rimliga och användbara igenkänningsnivåer. Speciellt för ett halvautomatiskt system där användaren har sista ordet om vem personen på bilden faktiskt är.</p><p>Med ett galleri bestående av 85 personer och endast en referensbild per person nådde systemet en igenkänningsgrad på 60% på en svårklassificerad serie testbilder. Totalt 73% av gångerna var den rätta individen inom de fyra främsta gissningarna.</p><p>Att lägga till extra referensbilder till galleriet höjer igenkänningsgraden rejält, till nästan 75% för helt korrekta gissningar och till 83,5% för topp fyra. Detta visar att en strategi där inmatade bilder läggs till som referensbilder i galleriet efterhand som de identifieras skulle löna sig ordentligt och göra systemet bättre efter hand likt en inlärningsprocess.</p><p>Detta exjobb belönades med pris för "Bästa industrirelevanta bidrag" vid Svenska sällskapet för automatiserad bildanalys årliga konferens i Lund, 13-14 mars 2008.</p> / <p>Applying face recognition directly on a mobile phone is a challenging proposal due to the unrestrained nature of input images and limitations in memory and processor capabilities.</p><p>A robust, fully automatic recognition system for this environment is still a far way off. However, results show that using local feature extraction and a warping scheme to reduce pose variation problems, it is possible to capitalize on high error tolerance and reach reasonable recognition rates, especially for a semi-automatic classification system where the user has the final say.</p><p>With a gallery of 85 individuals and only one gallery image per individual available the system is able to recognize close to 60 % of the faces in a very challenging test set, while the correct individual is in the top four guesses 73% of the time.</p><p>Adding extra reference images boosts performance to nearly 75% correct recognition and 83.5% in the top four guesses. This suggests a strategy where extra reference images are added one by one after correct classification, mimicking an online learning strategy.</p>

published_or_final_version / abstract / Computer Science / Doctoral / Doctor of Philosophy

The general theme running throughout this study is the enhancement of step functions which have been degraded by blur and/or additive noise in some form or another. We deal with step functions in both one and two dimensions. The two main areas of study are i. The enhancement of Synthetic Aperture Radar data. This is data which can be thought of some form of step function in two dimensions, and, ii. The enhancement of one dimensional step functions which have been degraded by both blur and additive noise. Although (i) is very specific to Synthetic Aperture Radar data (ii) is far more general and can be applied to any such data in this general category of steps. In fact a very wide range of problems can be thought of within the general context of being step-related. We describe and develop several methods is this study to deal with such problems.

No description available.

A controlled laboratory experiment was undertaken to simulate varying swash zone characteristics and sensor-target geometry found in digital images collected by ARGUS coastal imaging systems. Using a hyperspectral sensor, reflectance data were integrated over the respective red, blue and green wavelengths corresponding to a standard ARGUS video imaging sensor. The dominant swash zone parameters affecting shoreline detection were found to be the presence or absence of surface foam, site-specific sediment characteristics (especially colour), and water depth. Winter versus summer solar elevation and the sensor zenith were also found to affect the cross-shore location of the detected waterline. With this new information, site- and time-specific corrections can be applied to coastal digital imagery, to improve the confidence of shoreline detection.

<p>I examensarbetet studerades bildutveckling som även jämförts med författarens egen uppväxtmiljö.</p><p>Metoden har varit en litteraturstudie som behandlar ämnet estetiska uttrycksformer och kreativ uppväxt. Därtill har en granskning av författarens uppväxtmiljö gällande möjlighet till övande av kreativ förmåga tagits upp i relation till personlig utveckling.</p><p>Jämförelse har gjorts med stadieteorier om utvecklande av barns bildanvändning.</p><p>Genom dokumenterade av författarens egna bilder under tidiga år visades bildutveckling i de olika teckningsutvecklingsstadierna.</p><p>Slutsatsen är att kreativ förmåga påverkas sannolikt av uppfostran fylld med möjligheten att få måla och teckna, något som bildlärare kan utveckla i arbetet med barn.</p><p>Behov att som blivande lärare integrera bilden i de teoretiska ämnena kan utveckla dessa möjligheter ytterligare.</p>

<p>This thesis focuses on the development of methods for fusion of information from medical brain scans. The concept of medical image fusion refers to the process of extracting and utilising information from several scans simultaneously in the analysis and diagnosis of patients.</p><p>One very important part of the fusion process is the image registration, which is used to find a mapping or transformation of points from one image to the corresponding points in another image. This can, for example, be used to correct for relative movements between patient examinations, thus, making direct comparisons between different scans possible. Furthermore, the registration can be used to map images from different individuals into a common standard anatomy. This is important, since it enables comparisons between the individuals and also between whole groups of individuals. In the thesis, both methods to be used for registration between scans from the same individual and for scans from different individuals are presented.</p><p>Another part of the thesis is directed towards analysis of brain scans. Most of the methods are based on a computerised brain atlas, which defines a standardised mapping of the brain into sub-regions. These regions are either anatomical or functional and can be used for a more detailed analysis of the brain scan. The presented methods cover general methods for comparisons of single patients with groups of individuals, methods for feature calculations from brain atlas defined regions, and methods for extraction of more advanced features for automatic classification of brain scans.</p><p>Furthermore, image visualisation is always an important part in medical imaging. This is because the constantly increasing amount of medical information demands more advanced visualisation techniques to enhance and aid the interpretation of the data. The methods presented in this thesis are focused on combined visualisation of multiple brain scans, which is useful when scans expressing different types of information are available. For instance, a combined visualisation can be helpful to detect anatomical regions of specific functional importance in the brain.</p>

<p>This thesis presents work in digital image cytometry applied to fluorescence microscope images of cultivated cells. Focus has been on the development and compilation of robust image analysis tools, enabling quantitative measurements of various properties of cells and cell structures. A significant part of the work has consisted of developing robust segmentation methods for fluorescently labelled cells. This, in combination with effort applied in the areas of feature extraction and statistical data analysis, has enabled the compilation of a complete chain of processing steps to produce a system capable of performing fully automatic segmentation and classification of fluorescently labelled cells according to their level of activation.</p><p>Two sequences of processing steps, both leading to automatic cytoplasm segmentation of fluorescence microscopy cell images are presented. In one of the sequences, an additional image of the nuclei of the cells is segmented. The nuclei are then used as seeds for the segmentation of the cytoplasm image. This solves the problem of over-segmentation of the cytoplasms in an efficient way. The other sequence uses merge and split algorithms on the cytoplasm image, in conjunction with statistical analysis of descriptive features. This analysis is used in a feedback system to improve the segmentation performance, and to give an overall quality measure of the segmentation.</p><p>A classification method that separates individual cells into three classes, depending on their level of activation, is described. The method is based on analysis of time series of images. Using both general purpose features and carefully designed problem specific features, in combination with a floating feature selection procedure, a Bayesian classifier is built. Evaluation showed that the performance of the fully automatic classification procedure was very close to the performance of skilled manual classification.</p><p>A novel method for performing estimation of intensity nonuniformites of microscope images is presented. Methods to solve many other problems related to image analysis of cell images are discussed and evaluated. All methods presented in this work are applicable to real-world situations. The two main projects of the thesis work have been performed in close cooperation with and according to demands of the biomedical industry.</p>