Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

A concurrent region growing algorithm guided by circumscribed contours

Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach

Interfície gràfica per a la valoració d'operadors de preprocessat d'imatge en imatges d'ultrasò

El càncer de mama és una de les causes de més mortalitat entreles dones dels països desenvolupats. És tractat d'una maneramés eficient quan es fa una detecció precoç, on les tècniques d'imatge són molt importants. Una de les tècniques d'imatge més utilitzades després dels raigs-X són els ultrasons. A l'hora de fer un processat d'imatges d'ultrasò, els experts en aquest camp es troben amb una sèrie de limitacions en el moment d'utilitzar uns filtrats per les imatges, quan es fa ús de determinades eines. Una d'aquestes limitacions consisteix en la falta d'interactivitat que aquestes ens ofereixen. Per tal de solventar aquestes limitacions, s'ha desenvolupat una eina interactiva que permet explorar el mapa de paràmetres visualitzant el resultat del filtrat en temps real, d'una manera dinàmica i intuïtiva. Aquesta eina s'ha desenvolupat dins l'entorn de visualització d'imatge mèdica MeVisLab. El MeVisLab és un entorn molt potent i modular pel desenvolupament d'algorismes de processat d'imatges, visualització i mètodes d'interacció, especialment enfocats a la imatge mèdica. A més del processament bàsic d'imatges i de mòduls de visualització, inclou algorismes avançats de segmentació, registre i moltes análisis morfològiques i funcionals de les imatges.S'ha dut a terme un experiment amb quatre experts que, utilitzantl'eina desenvolupada, han escollit els paràmetres que creien adientsper al filtrat d'una sèrie d'imatges d'ultrasò. En aquest experiments'han utilitzat uns filtres que l'entorn MeVisLab ja té implementats:el Bilateral Filter, l'Anisotropic Difusion i una combinació d'un filtrede Mediana i un de Mitjana.Amb l'experiment realitzat, s'ha fet un estudi dels paràmetres capturats i s'han proposat una sèrie d'estimadors que seran favorables en la majoria dels casos per dur a terme el preprocessat d'imatges d'ultrasò

Unsupervised visual object categorization

The number of digital images has been increasing exponentially in the last few years. People have problems managing their image collections and finding a specific image. An automatic image categorization system could help them to manage images and find specific images. In this thesis, an unsupervised visual object categorization system was implemented to categorize a set of unknown images. The system is unsupervised, and hence, it does not need known images to train the system which needs to be manually obtained. Therefore, the number of possible categories and images can be huge. The system implemented in the thesis extracts local features from the images. These local features are used to build a codebook. The local features and the codebook are then used to generate a feature vector for an image. Images are categorized based on the feature vectors. The system is able to categorize any given set of images based on the visual appearance of the images. Images that have similar image regions are grouped together in the same category. Thus, for example, images which contain cars are assigned to the same cluster. The unsupervised visual object categorization system can be used in many situations, e.g., in an Internet search engine. The system can categorize images for a user, and the user can then easily find a specific type of image.

An octree isosurface codification based on discrete planes

Describes a method to code a decimated model of an isosurface on an octree representation while maintaining volume data if it is needed. The proposed technique is based on grouping the marching cubes (MC) patterns into five configurations according the topology and the number of planes of the surface that are contained in a cell. Moreover, the discrete number of planes on which the surface lays is fixed. Starting from a complete volume octree, with the isosurface codified at terminal nodes according to the new configuration, a bottom-up strategy is taken for merging cells. Such a strategy allows one to implicitly represent co-planar faces in the upper octree levels without introducing any error. At the end of this merging process, when it is required, a reconstruction strategy is applied to generate the surface contained in the octree intersected leaves. Some examples with medical data demonstrate that a reduction of up to 50% in the number of polygons can be achieved

Fourier-based registration for robust forward-looking sonar mosaicing in low-visibility underwater environments

Vehicle operations in underwater environments are often compromised by poor visibility conditions. For instance, the perception range of optical devices is heavily constrained in turbid waters, thus complicating navigation and mapping tasks in environments such as harbors, bays, or rivers. A new generation of high-definition forward-looking sonars providing acoustic imagery at high frame rates has recently emerged as a promising alternative for working under these challenging conditions. However, the characteristics of the sonar data introduce difficulties in image registration, a key step in mosaicing and motion estimation applications. In this work, we propose the use of a Fourier-based registration technique capable of handling the low resolution, noise, and artifacts associated with sonar image formation. When compared to a state-of-the art region-based technique, our approach shows superior performance in the alignment of both consecutive and nonconsecutive views as well as higher robustness in featureless environments. The method is used to compute pose constraints between sonar frames that, integrated inside a global alignment framework, enable the rendering of consistent acoustic mosaics with high detail and increased resolution. An extensive experimental section is reported showing results in relevant field applications, such as ship hull inspection and harbor mapping

Optimització de la tècnica del miralls màgics a partir de mesures de teoria de la informació

La visualització científica estudia i defineix algorismes i estructures de dades que permeten fer comprensibles conjunts de dades a través d’imatges. En el cas de les aplicacions mèdiques les dades que cal interpretar provenen de diferents dispositius de captació i es representen en un model de vòxels. La utilitat d’aquest model de vòxels depèn de poder-lo veure des del punt de vista ideal, és a dir el que aporti més informació. D’altra banda, existeix la tècnica dels Miralls Màgics que permet veure el model de vòxels des de diferents punts de vista alhora i mostrant diferents valors de propietat a cada mirall. En aquest projecte implementarem un algorisme que permetrà determinar el punt de vista ideal per visualitzar un model de vòxels així com també els punts de vista ideals per als miralls per tal d’aconseguir el màxim d’informació possible del model de vòxels. Aquest algorisme es basa en la teoria de la informació per saber quina és la millor visualització. L’algorisme també permetrà determinar l’assignació de colors òptima per al model de vòxels

Oliopohjainen konenäkösovelluskehys

Monet teollisuuden konenäkö- ja hahmontunnistusongelmat ovat hyvin samantapaisia, jolloin prototyyppisovelluksia suunniteltaessa voitaisiin hyödyntää pitkälti samoja komponentteja. Oliopohjaiset sovelluskehykset tarjoavat erinomaisen tavan nopeuttaa ohjelmistokehitystä uudelleenkäytettävyyttä parantamalla. Näin voidaan sekä mahdollistaa konenäkösovellusten laajempi käyttö että säästää kustannuksissa. Tässä työssä esitellään konenäkösovelluskehys, joka on perusarkkitehtuuriltaan liukuhihnamainen. Ylätason rakenne koostuu sensorista, datankäsittelyoperaatioista, piirreirrottimesta sekä luokittimesta. Itse sovelluskehyksen lisäksi on toteutettu joukko kuvankäsittely- ja hahmontunnistusoperaatioita. Sovelluskehys nopeuttaa selvästi ohjelmointityötä ja helpottaa uusien kuvankäsittelyoperaatioiden lisää mistä.

Computational visual quality of digitally printed images

The problem of understanding how humans perceive the quality of a reproduced image is of interest to researchers of many fields related to vision science and engineering: optics and material physics, image processing (compression and transfer), printing and media technology, and psychology. A measure for visual quality cannot be defined without ambiguity because it is ultimately the subjective opinion of an “end-user” observing the product. The purpose of this thesis is to devise computational methods to estimate the overall visual quality of prints, i.e. a numerical value that combines all the relevant attributes of the perceived image quality. The problem is limited to consider the perceived quality of printed photographs from the viewpoint of a consumer, and moreover, the study focuses only on digital printing methods, such as inkjet and electrophotography. The main contributions of this thesis are two novel methods to estimate the overall visual quality of prints. In the first method, the quality is computed as a visible difference between the reproduced image and the original digital (reference) image, which is assumed to have an ideal quality. The second method utilises instrumental print quality measures, such as colour densities, measured from printed technical test fields, and connects the instrumental measures to the overall quality via subjective attributes, i.e. attributes that directly contribute to the perceived quality, using a Bayesian network. Both approaches were evaluated and verified with real data, and shown to predict well the subjective evaluation results.

Puoliautomaattinen silmänpohjakuvien tulkintatyökalu

Tässä tutkimuksessa toteutettiin uusi versio aikaisemmin tuotetusta työkalusta merkintöjen tekemiseksi pääasiassa silmänpohjakuviin. Tarkoituksena oli toteuttaa kuvankäsittelyyn perustuvia aputoimintoja kuvien valaistuksenkorjaamiseksi, sekä korostaa lääkärille mahdollisia diabeettiseen retinopatiaan kuuluvia löydöksiä. Kuvien annotoinnin helpottamiseksi toteutettiin kaksi menetelmää valaistuksenkorjaamiseksi: yksiulotteinen käyrämenetelmä sekä värikanavien ominaisuuksia hyödyntävä menetelmä. Kuvien annotoinin helpottamiseksi toteutettiin kuvan vihreän kanavan jakaumaan perustuva aputoiminto, joka pyrkii korostamaan mahdollisia diabeettiseen retinopatiaan kuuluvia löydöksiä.

Pulsatile Blood Flow Simulations in Computed Tomography(CT) Scan-Based and Idealized Geometries of Human Aorta

Blood flow in human aorta is an unsteady and complex phenomenon. The complex patterns are related to the geometrical features like curvature, bends, and branching and pulsatile nature of flow from left ventricle of heart. The aim of this work was to understand the effect of aorta geometry on the flow dynamics. To achieve this, 3D realistic and idealized models of descending aorta were reconstructed from Computed Tomography (CT) images of a female patient. The geometries were reconstructed using medical image processing code. The blood flow in aorta was assumed to be laminar and incompressible and the blood was assumed to be Newtonian fluid. A time dependent pulsatile and parabolic boundary condition was deployed at inlet. Steady and unsteady blood flow simulations were performed in real and idealized geometries of descending aorta using a Finite Volume Method (FVM) code. Analysis of Wall Shear Stress (WSS) distribution, pressure distribution, and axial velocity profiles were carried out in both geometries at steady and unsteady state conditions. The results obtained in thesis work reveal that the idealization of geometry underestimates the values of WSS especially near the region with sudden change of diameter. However, the resultant pressure and velocity in idealized geometry are close to those in real geometry

Computational Evaluation of Print Unevenness According to Human Vision

Print quality and the printability of paper are very important attributes when modern printing applications are considered. In prints containing images, high print quality is a basic requirement. Tone unevenness and non uniform glossiness of printed products are the most disturbing factors influencing overall print quality. These defects are caused by non ideal interactions of paper, ink and printing devices in high speed printing processes. Since print quality is a perceptive characteristic, the measurement of unevenness according to human vision is a significant problem. In this thesis, the mottling phenomenon is studied. Mottling is a printing defect characterized by a spotty, non uniform appearance in solid printed areas. Print mottle is usually the result of uneven ink lay down or non uniform ink absorption across the paper surface, especially visible in mid tone imagery or areas of uniform color, such as solids and continuous tone screen builds. By using existing knowledge on visual perception and known methods to quantify print tone variation, a new method for print unevenness evaluation is introduced. The method is compared to previous results in the field and is supported by psychometric experiments. Pilot studies are made to estimate the effect of optical paper characteristics prior to printing, on the unevenness of the printed area after printing. Instrumental methods for print unevenness evaluation have been compared and the results of the comparison indicate that the proposed method produces better results in terms of visual evaluation correspondence. The method has been successfully implemented as ail industrial application and is proved to be a reliable substitute to visual expertise.

Advanced orbital pipe welding

Since the introduction of automatic orbital welding in pipeline application in 1961, significant improvements have been obtained in orbital pipe welding systems. Requirement of more productive welding systems for pipeline application forces manufacturers to innovate new advanced systems and welding processes for orbital welding method. Various methods have been used to make welding process adaptive, such as visual sensing, passive visual sensing, real-time intelligent control, scan welding technique, multi laser vision sensor, thermal scanning, adaptive image processing, neural network model, machine vision, and optical sensing. Numerous studies are reviewed and discussed in this Master’s thesis and based on a wide range of experiments which already have been accomplished by different researches the vision sensor are reported to be the best choice for adaptive orbital pipe welding system. Also, in this study the most welding processes as well as the most pipe variations welded by orbital welding systems mainly for oil and gas pipeline applications are explained. The welding results show that Gas Metal Arc Welding (GMAW) and its variants like Surface Tension Transfer (STT) and modified short circuit are the most preferred processes in the welding of root pass and can be replaced to the Gas Tungsten Arc Welding (GTAW) in many applications. Furthermore, dual-tandem gas metal arc welding technique is currently considered the most efficient method in the welding of fill pass. Orbital GTAW process mostly is applied for applications ranging from single run welding of thin walled stainless tubes to multi run welding of thick walled pipes. Flux cored arc welding process is faster process with higher deposition rate and recently this process is getting more popular in pipe welding applications. Also, combination of gas metal arc welding and Nd:YAG laser has shown acceptable results in girth welding of land pipelines for oil and gas industry. This Master’s thesis can be implemented as a guideline in welding of pipes and tubes to achieve higher quality and efficiency. Also, this research can be used as a base material for future investigations to supplement present finding.

Application of Computational Fluid Dynamics in Modeling Blood Flow in Human Thoracic Aorta

The aim of this study was to simulate blood flow in thoracic human aorta and understand the role of flow dynamics in the initialization and localization of atherosclerotic plaque in human thoracic aorta. The blood flow dynamics in idealized and realistic models of human thoracic aorta were numerically simulated in three idealized and two realistic thoracic aorta models. The idealized models of thoracic aorta were reconstructed with measurements available from literature, and the realistic models of thoracic aorta were constructed by image processing Computed Tomographic (CT) images. The CT images were made available by South Karelia Central Hospital in Lappeenranta. The reconstruction of thoracic aorta consisted of operations, such as contrast adjustment, image segmentations, and 3D surface rendering. Additional design operations were performed to make the aorta model compatible for the numerical method based computer code. The image processing and design operations were performed with specialized medical image processing software. Pulsatile pressure and velocity boundary conditions were deployed as inlet boundary conditions. The blood flow was assumed homogeneous and incompressible. The blood was assumed to be a Newtonian fluid. The simulations with idealized models of thoracic aorta were carried out with Finite Element Method based computer code, while the simulations with realistic models of thoracic aorta were carried out with Finite Volume Method based computer code. Simulations were carried out for four cardiac cycles. The distribution of flow, pressure and Wall Shear Stress (WSS) observed during the fourth cardiac cycle were extensively analyzed. The aim of carrying out the simulations with idealized model was to get an estimate of flow dynamics in a realistic aorta model. The motive behind the choice of three aorta models with distinct features was to understand the dependence of flow dynamics on aorta anatomy. Highly disturbed and nonuniform distribution of velocity and WSS was observed in aortic arch, near brachiocephalic, left common artery, and left subclavian artery. On the other hand, the WSS profiles at the roots of branches show significant differences with geometry variation of aorta and branches. The comparison of instantaneous WSS profiles revealed that the model with straight branching arteries had relatively lower WSS compared to that in the aorta model with curved branches. In addition to this, significant differences were observed in the spatial and temporal profiles of WSS, flow, and pressure. The study with idealized model was extended to study blood flow in thoracic aorta under the effects of hypertension and hypotension. One of the idealized aorta models was modified along with the boundary conditions to mimic the thoracic aorta under the effects of hypertension and hypotension. The results of simulations with realistic models extracted from CT scans demonstrated more realistic flow dynamics than that in the idealized models. During systole, the velocity in ascending aorta was skewed towards the outer wall of aortic arch. The flow develops secondary flow patterns as it moves downstream towards aortic arch. Unlike idealized models, the distribution of flow was nonplanar and heavily guided by the artery anatomy. Flow cavitation was observed in the aorta model which was imaged giving longer branches. This could not be properly observed in the model with imaging containing a shorter length for aortic branches. The flow circulation was also observed in the inner wall of the aortic arch. However, during the diastole, the flow profiles were almost flat and regular due the acceleration of flow at the inlet. The flow profiles were weakly turbulent during the flow reversal. The complex flow patterns caused a non-uniform distribution of WSS. High WSS was distributed at the junction of branches and aortic arch. Low WSS was distributed at the proximal part of the junction, while intermedium WSS was distributed in the distal part of the junction. The pulsatile nature of the inflow caused oscillating WSS at the branch entry region and inner curvature of aortic arch. Based on the WSS distribution in the realistic model, one of the aorta models was altered to induce artificial atherosclerotic plaque at the branch entry region and inner curvature of aortic arch. Atherosclerotic plaque causing 50% blockage of lumen was introduced in brachiocephalic artery, common carotid artery, left subclavian artery, and aortic arch. The aim of this part of the study was first to study the effect of stenosis on flow and WSS distribution, understand the effect of shape of atherosclerotic plaque on flow and WSS distribution, and finally to investigate the effect of lumen blockage severity on flow and WSS distributions. The results revealed that the distribution of WSS is significantly affected by plaque with mere 50% stenosis. The asymmetric shape of stenosis causes higher WSS in branching arteries than in the cases with symmetric plaque. The flow dynamics within thoracic aorta models has been extensively studied and reported here. The effects of pressure and arterial anatomy on the flow dynamic were investigated. The distribution of complex flow and WSS is correlated with the localization of atherosclerosis. With the available results we can conclude that the thoracic aorta, with complex anatomy is the most vulnerable artery for the localization and development of atherosclerosis. The flow dynamics and arterial anatomy play a role in the localization of atherosclerosis. The patient specific image based models can be used to diagnose the locations in the aorta vulnerable to the development of arterial diseases such as atherosclerosis.