With the emergence of new imaging techniques, researchers are always eager to push the boundaries by examining objects either smaller or further away than what was previously possible. The development of image analysis techniques has greatly helped to introduce objectivity and coherence in measurements and decision making. It has become an essential tool for facilitating both large-scale quantitative studies and qualitative research. In this Thesis, methods were developed for analysis of low-resolution (in respect to the size of the imaged objects) three-dimensional (3D) images with low signal-to-noise ratios (SNR) applied to images from cryo-electron tomography (cryo-ET) and fluorescence microscopy (FM). The main focus is on methods of low complexity, that take into account both grey-level and shape information, to facilitate large-scale studies. Methods were developed to localise and represent complex macromolecules in images from cryo-ET. The methods were applied to Immunoglobulin G (IgG) antibodies and MET proteins. The low resolution and low SNR required that grey-level information was utilised to create fuzzy representations of the macromolecules. To extract structural properties, a method was developed to use grey-level-based distance measures to facilitate decomposition of the fuzzy representations into sub-domains. The structural properties of the MET protein were analysed by developing a analytical curve representation of its stalk. To facilitate large-scale analysis of structural properties of nerve cells, a method for tracing neurites in FM images using local path-finding was developed. Both theoretical and implementational details of computationally heavy approaches were examined to keep the time complexity low in the developed methods. Grey-weighted distance definitions and various aspects of their implementations were examined in detail to form guidelines on which definition to use in which setting and which implementation is the fastest. Heuristics were developed to speed up computations when calculating grey-weighted distances between two points. The methods were evaluated on both real and synthetic data and the results show that the methods provide a step towards facilitating large-scale studies of images from both cryo-ET and FM.

In brachytherapy, radiation therapy is performed by placing the radiation source into or very close to the tumour. When calculating the absorbed dose, water is often used as the radiation transport and dose scoring medium for soft tissues and this leads to inaccuracies. The iterative reconstruction algorithm DIRA is under development at the Center for Medical Imaging Science and Visualization, Linköping University. DIRA uses dual-energy CT to decompose tissues into different doublets and triplets of base components for a better absorbed dose estimation. To accurately determine mass fractions of these base components for different tissues, the tissues needs to be identified in the image. The aims of this master thesis are: (i) Find an automated segmentation algorithm in CT that best segments the male pelvis. (ii) Implement a segmentation algorithm that can be used in DIRA. (iii) Implement a fully automatic segmentation algorithm. Seven segmentation methods were tested in Matlab using images obtained from Linköping University Hospital. The methods were: active contours, atlas based registration, graph cuts, level set, region growing, thresholding and watershed. Four segmentation algorithms were selected for further analysis: phase based atlas registration, region growing, thresholding and active contours without edges. The four algorithms were combined and supplemented with other image analysis methods to form a fully automated segmentation algorithm that was implemented in DIRA. The newly developed algorithm (named MK2014) was sufficiently stable for pelvic image segmentation with a mean computational time of 45.3 s and a mean Dice similarity coefficient of 0.925 per 512×512 image. The performance of MK2014 tested on a simplified anthropomorphic phantom in DIRA gave promising result. Additional tests with more realistic phantoms are needed to confirm the general applicability of MK2014 in DIRA.

Medical imaging has become the key to access inside human body for the purpose of diagnosis and treatment planning. In order to understand the effectiveness of planned treatment following the diagnosis, treated body part may have to be monitored several times during a period of time. Information gained from successive imaging of body part provides guidance to next step of treatment. Comparison of images or datasets taken at different times requires registration of these images or datasets since the same conditions may not be provided at all times. Accurate segmentation of the body part under treatment is needed while comparing medical images to achieve quantitative and qualitative measurements. This segmentation task enables two dimensional and three dimensional visualizations of the region which also aid in directing the planning strategy. In this thesis, several segmentation algorithms are investigated and a hybrid segmentation algorithm is developed in order to segment bone tissue out of head CT slices for orthodontic treatment planning. Using the developed segmentation algorithm, three dimensional visualizations of segmented bone tissue out of head CT slices of two patients are obtained. Visualizations are obtained using the MATLAB Computer software&amp / #8217 / s visualization library. Besides these, methods are developed for automatic registration of twodimensional and three-dimensional CT images taken at different time periods. These methods are applied to real and synthetic data. Algorithms and methods used in this thesis are also implemented in MATLAB computer program.

The ability of robotic units to navigate various terrains is critical to the advancement of robotic operation in real world environments. Next generation robots will need to adapt to their environment in order to accomplish tasks that are either too hazardous, too time consuming, or physically impossible for human-beings. Such tasks may include accurate and rapid explorations of various planets or potentially dangerous areas on planet Earth. This research investigates a navigation control methodology for a wheel-legged robot based on active vision. The method presented is designed to control the reconfigurability of the robot (i.e. control the usage of the wheels and legs), depending upon the obstacle/terrain, based on perception. Surface estimation for robot reconfigurability is implemented using a region growing method and a characterization and traversability assessment generated from camera data. As a result, a mathematical approach that directs necessary navigation behavior is implemented to control robot mobility. The hybrid wheeled-legged rover possesses a four-legged or six-legged walking system as well as a four-wheeled mobility system.

Automatic segmentation of human organs allows more accurate calculation of organ doses in radiationtreatment planning, as it adds prior information about the material composition of imaged tissues. For instance, the separation of tissues into bone, adipose tissue and remaining soft tissues allows to use tabulated material compositions of those tissues. This approximation is not perfect because of variability of tissue composition among patients, but is still better than no approximation at all. Another use for automated tissue segmentationis in model based iterative reconstruction algorithms. An example of such an algorithm is DIRA, which is developed at the Medical Radiation Physics and the Center for Medical Imaging Science and Visualization(CMIV) at Linköpings University. DIRA uses dual-energy computed tomography (DECT) data to decompose patient tissues into two or three base components. So far DIRA has used the MK2014 algorithm which segments human pelvis into bones, adipose tissue, gluteus maximus muscles and the prostate. One problem was that MK2014 was limited to 2D and it was not very robust. Aim: The aim of this thesis work was to extend the MK2014 to 3D as well as to improve it. The task was structured to the following activities: selection of suitable segmentation algorithms, evaluation of their results and combining of those to an automated segmentation algorithm. Of special interest was image registration usingthe Morphon. Methods: Several different algorithms were tested.  For instance: Otsu's method followed by threshold segmentation; histogram matching followed by threshold segmentation, region growing and hole-filling; affine phase-based registration and the Morphon. The best-performing algorithms were combined into the newly developed JJ2016. Results: For the segmentation of adipose tissue and the bones in the eight investigated data sets, the JJ2016 algorithm gave better results than the MK2014. The better results of the JJ2016 were achieved by: (i) a new segmentation algorithm for adipose tissue which was not affected by the amount of air surrounding the patient and segmented smaller regions of adipose tissue and (ii) a new filling algorithm for connecting segments of compact bone. The JJ2016 algorithm also estimates a likely position for the prostate and the rectum by combining linear and non-linear phase-based registration for atlas based segmentation. The estimated position (center point) was in most cases close to the true position of the organs. Several deficiencies of the MK2014 algorithm were removed but the improved version (MK2014v2) did not perform as well as the JJ2016. Conclusions: JJ2016 performed well for all data sets. The JJ2016 algorithm is usable for the intended application, but is (without further improvements) too slow for interactive usage. Additionally, a validation of the algorithm for clinical use should be performed on a larger number of data sets, covering the variability of patients in shape and size.

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Microarray technology enables simultaneous gene expression level monitoring for thousands of genes. While this technology has now been recognized as a powerful and cost-effective tool for large-scale analysis, the many systematic sources of experimental variations introduce inherent errors in the extracted data. Data is gathered by processing scanned images of microarray slides. Therefore robust image processing is particularly important and has a large impact on downstream analysis. The processing of the scanned images can be subdivided in three phases: gridding, segmentation and data extraction. To measure the gene expression levels, the processing of cDNA microarray images must overcome a large set of issues in these three phases that motivates this study. This study presents automatic gridding methods and compares their performances. Two segmentation techniques already used, the Seeded Region Growing Algorithm and the Mann-Whitney Test, are examined. We present limitations of these techniques. Finally, we studied the data extraction method used in MicroArray Suite (MS), a microarray analysis software, via synthetic images and explain its intricacies. / Master of Science

<p>Laser scanners in combination with devices for accurate orientation like Coordinate Measuring Machines (CMM) are often used in Geometric Reverse Engineering (GRE) to measure point data. The industrial robot as a device for orientation has relatively low accuracy but the advantage of being numerically controlled, fast, flexible, rather cheap and compatible with industrial environments. It is therefore of interest to investigate if it can be used in this application.</p><p>This thesis will describe a measuring system consisting of a laser profile scanner mounted on an industrial robot with a turntable. It will also give an introduction to Geometric Reverse Engineering (GRE) and describe an automatic GRE process using this measuring system. The thesis also presents a detailed accuracy analysis supported by experiments that show how 2D profile data can be used to achieve a higher accuracy than the basic accuracy of the robot. The core topic of the thesis is the investigation of a new technique for planar segmentation. The new method is implemented in the GRE system and compared with an implementation of a more traditional method.</p><p>Results from practical experiments show that the new method is much faster while equally accurate or better.</p>

Τα τελευταία χρόνια, η δημοτικότητα του διαδικτύου αυξάνεται ολοένα και περισσότερο και σε συνδυασμό με την κινηματογραφική βιομηχανία που ανθίζει με γρήγορους ρυθμούς , έχει σαν αποτέλεσμα έναν τεράστιο αριθμό βίντεο κοινής χρήσης στο διαδίκτυο και μια πληθώρα κινηματογραφικών ταινιών, στα οποία έχει άμεση πρόσβαση μεγάλη μερίδα του πληθυσμού, συμπεριλαμβανομένων και διάφορων ευαίσθητων κοινωνικών ομάδων, παραδείγματος χάρη παιδιά και εφήβους. Η προστασία τέτοιων ατόμων αλλά και η επιθυμία γνώσης του περιεχομένου ενός βίντεο δημιούργησε την αναγκαιότητα ανάπτυξης αποτελεσματικών, αυτόματων ανιχνευτών βίας.Στην παρούσα διπλωματική παρουσιάζονται οι μέθοδοι που έχουν προταθεί στο συγκεκριμένο πεδίο. Στην συνέχεια, υιοθετείται μια εκ των μεθόδων και αναπτύσσεται αλγόριθμος, με σκοπό τη μελέτη της απόδοσης του. / In recent years, the popularity of the internet growing more and more.This results a huge number of video sharing on the internet and a plethora of films. A large portion of population has direct access in such videos,including sensitive and different social groups , for example children and adolescents . The protection of such persons and the desire knowing the content of a video, created the necessity to develop efficient , automated violence detectors.In this dissertation we present methods that have been proposed in this field . Then , we have adopted one of the methods and we have developed an algorithm in order to study its accuracy.