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.

Teknologiska framsteg påverkar tillverkningsindustrin genom att integrera tester för kretskortens status, lödning och elektriska egenskaper. En pick-and-place-maskin används för att verifiera komponentpositioner på kretskortet, men underhåll och re-paration av dessa maskiner medför stora kostnader. Industry 4.0 introducerar auto-matiseringslösningar som Internet of Things, Big Data, dataanalys och cybersäker-het, vilket kräver uppgradering av utrustning. Att erbjuda prisvärda uppgraderingar för äldre maskiner är avgörande för små och medelstora företags konkurrenskraft. Validering av kretskortkomponenterna på ett kostnadseffektiv och tillförlitligt sätt kan optimera kretskortsindustri.Det finns idag framgångsrika metoder för att lösa liknande problem. Konvolutionella neurala nätverk, finkornig bildigenkänning, funktionsmatchning samt funktions-extraktion är exempel på dessa. För att verifiera korrekt positionering av en krets-kortskomponent utnyttjas en automatisk maskin som systematiskt inspekterar kretskortet med hjälp av en pick-and-place fil som inkluderar exakta koordinater för varje position.Denna studie använder bildigenkänning för att finna en ekonomisk implementerbar lösning på identifiering av kretskortskomponenter. Detta för att undersöka om mo-biltelefonkameran är en möjlig implementationslösning för små till medelstora före-tag att identifiera kretskort. En mobilkamera användes för att ta bilder på kretskor-ten. Detta gjordes i varierande ljussättning, vinklar samt avstånd från kretskortet. En algoritm skapades för att undersöka ifall komponenterna är korrekt placerade på kretskortet. Segmentering, morfologiska processer och kunskapsbaserade metoder används i denna algoritm.Resultatet tyder på att det är en lämplig lösning att använda bildbehandling för att identifiera kretskortskomponenters position. Att identifiera korrekt satta eller fel-aktigt satta komponenter är möjligt förutsatt att bilderna är tagna med referensnära inställningar. Därav kan små till medelstora företag använda sig utav denna lösning för att få en kostnadseffektiv samt tillförlitlig identifiering. / Technological advances are impacting the manufacturing industry by integrating tests for circuit board status, soldering, and electrical properties. A pick-and-place machine is used to verify components positions on the circuit board, but mainte-nance and repair of these machines incurs large costs. Industry 4.0 introduces auto-mation solutions such as the Internet of Things, Big Data, data analysis, and cyberse-curity, which require equipment upgrades. Offering affordable upgrades for older machines is critical to the competitiveness of small and medium-sized businesses. Validation of the circuit board components in a cost-effective and reliable way can optimize the circuit board industry.Today there are successful methods of solving similar problems. Convolutional neu-ral networks, fine-grained image recognition, feature matching, and feature extrac-tion are examples of these. To verify the correct positioning of a circuit board com-ponent, an automatic machine is used that systematically inspects the circuit board using a pick-and-place file that includes exact coordinates for each position.This study uses image recognition to find an economically implementable solution to the identification of printed circuit board components. This is to investigate whether the mobile phone camera is a possible implementation solution for small to me-dium-sized companies to identify circuit boards. The mobile phone camera was used to capture images of the circuit board. This was done in varying lighting, angles, and distance from the circuit board. An algorithm was created to check if the compo-nents are correctly placed on the circuit board. Segmentation, morphological pro-cesses, and knowledge-based methods are used in this algorithm.The result suggests that using image processing to identify the position of circuit board components is a suitable solution. Identifying correctly set or incorrectly set components is possible provided that the images are taken with reference-close set-tings. Therefore, small to medium-sized companies can use this solution to obtain cost-effective and reliable identification.

This thesis deals with the synthesis of anisotropic volumetric textures from a single 2D observation. We present variants of non parametric and multi-scale algorithms. Their main specificity lies in the fact that the 3D synthesis process relies on the sampling of a single 2D input sample, ensuring consistency in the different views of the 3D texture. Two types of approaches are investigated, both multi-scale and based on markovian hypothesis. The first category brings together a set of algorithms based on fixed-neighbourhood search, adapted from existing algorithms of texture synthesis from multiple 2D sources. The principle is that, starting from a random initialisation, the 3D texture is modified, voxel by voxel, in a deterministic manner, ensuring that the grey level local configurations on orthogonal slices containing the voxel are similar to configurations of the input image. The second category points out an original probabilistic approach which aims at reproducing in the textured volume the interactions between pixels learned in the input image. The learning is done by non-parametric Parzen windowing. Optimization is handled voxel by voxel by a deterministic ICM type algorithm. Several variants are proposed regarding the strategies used for the simultaneous handling of the orthogonal slices containing the voxel. These synthesis methods are first implemented on a set of structured textures of varied regularity and anisotropy. A comparative study and a sensitivity analysis are carried out, highlighting the strengths and the weaknesses of the different algorithms. Finally, they are applied to the simulation of volumetric textures of carbon composite materials, on nanometric scale snapshots obtained by transmission electron microscopy. The proposed experimental benchmark allows to evaluate quantitatively and objectively the performances of the different methods.

Ce mémoire traite de synthèse de textures volumiques anisotropes à partir d’une observation 2D unique. Nous présentons différentes variantes d’algorithmes non paramétriques et multi-échelles. Leur principale particularité réside dans le fait que le processus de synthèse 3D s’appuie sur l’échantillonnage d’une seule image 2D d’entrée, en garantissant la cohérence selon les différentes vues de la texture 3D. Deux catégories d’approches sont abordées, toutes deux multi-échelles et basées sur une hypothèse markovienne. La première catégorie regroupe un ensemble d’algorithmes dits de recherche de voisinages fixes, adaptés d’algorithmes existants de synthèses de textures volumiques à partir de sources 2D multiples. Le principe consiste, à partir d’une initialisation aléatoire, à modifier les voxels un par un, de façon déterministe, en s’assurant que les configurations locales de niveaux de gris sur des tranches orthogonales contenant le voxel sont semblables à des configurations présentes sur l’image d’entrée. La deuxième catégorie relève d’une approche probabiliste originale dont l’objectif est de reproduire, sur le volume texturé, les interactions entre pixels estimées sur l’image d’entrée. L’estimation est réalisée de façon non paramétrique par fenêtrage de Parzen. L’optimisation est gérée voxel par voxel, par un algorithme déterministe de type ICM. Différentes variantes sont proposées, relatives aux stratégies de gestion simultanée des tranches orthogonales contenant le voxel. Ces différentes méthodes sont d’abord mises en œuvre pour la synthèse d’un jeu de textures structurées, de régularité et d’anisotropie variées. Une analyse comparée et une étude de sensibilité sont menées, mettant en évidence les atouts et faiblesses des différentes approches. Enfin, elles sont appliquées à la simulation de textures volumiques de matériaux composites carbonés, à partir de clichés obtenus à l’échelle nanométrique par microscopie électronique à transmission. Le schéma expérimental proposé permet d’évaluer quantitativement et de façon objective les performances des différentes méthodes. / This thesis deals with the synthesis of anisotropic volumetric textures from a single 2D observation. We present variants of non parametric and multi-scale algorithms. Their main specificity lies in the fact that the 3D synthesis process relies on the sampling of a single 2D input sample, ensuring consistency in the different views of the 3D texture. Two types of approaches are investigated, both multi-scale and based on markovian hypothesis. The first category brings together a set of algorithms based on fixed-neighbourhood search, adapted from existing algorithms of texture synthesis from multiple 2D sources. The principle is that, starting from a random initialisation, the 3D texture is modified, voxel by voxel, in a deterministic manner, ensuring that the grey level local configurations on orthogonal slices containing the voxel are similar to configurations of the input image. The second category points out an original probabilistic approach which aims at reproducing in the textured volume the interactions between pixels learned in the input image. The learning is done by non-parametric Parzen windowing. Optimization is handled voxel by voxel by a deterministic ICM type algorithm. Several variants are proposed regarding the strategies used for the simultaneous handling of the orthogonal slices containing the voxel. These synthesis methods are first implemented on a set of structured textures of varied regularity and anisotropy. A comparative study and a sensitivity analysis are carried out, highlighting the strengths and the weaknesses of the different algorithms. Finally, they are applied to the simulation of volumetric textures of carbon composite materials, on nanometric scale snapshots obtained by transmission electron microscopy. The proposed experimental benchmark allows to evaluate quantitatively and objectively the performances of the different methods.