Segmentation and analysis of volume images, with applications

Digital image analysis is the field of extracting relevant information from digital images. Recent developments in imaging techniques have made 3-dimensional volume images more common. This has created a need to extend existing 2D image analysis tools to handle images of higher dimensions. Such extensions are usually not straightforward. In many cases, the theoretical and computational complexity of a problem increases dramatically when an extra dimension is added. A fundamental problem in image analysis is image segmentation, i.e., identifying and separating relevant objects and structures in an image. Accurate segmentation is often required for further processing and analysis of the image can be applied. Despite years of active research, general image segmentation is still seen as an unsolved problem. This mainly due to the fact that it is hard to identify objects from image data only. Often, some high-level knowledge about the objects in the image is needed. This high-level knowledge may be provided in different ways. For fully automatic segmentation, the high-level knowledge must be incorporated in the segmentation algorithm itself. In interactive applications, a human user may provide high-level knowledge by guiding the segmentation process in various ways. The aim of the work presented here is to develop segmentation and analysis tools for volume images. To limit the scope, the focus has been on two specific applications of volume image analysis: analysis of volume images of fibrous materials and interactive segmentation of medical images. The respective image analysis challenges of these two applications will be discussed. While the work has been focused on these two applications, many of the results presented here are applicable to other image analysis problems

Graph-based Methods for Interactive Image Segmentation

The subject of digital image analysis deals with extracting relevant information from image data, stored in digital form in a computer. A fundamental problem in image analysis is image segmentation, i.e., the identification and separation of relevant objects and structures in an image. Accurate segmentation of objects of interest is often required before further processing and analysis can be performed. Despite years of active research, fully automatic segmentation of arbitrary images remains an unsolved problem. Interactive, or semi-automatic, segmentation methods use human expert knowledge as additional input, thereby making the segmentation problem more tractable. The goal of interactive segmentation methods is to minimize the required user interaction time, while maintaining tight user control to guarantee the correctness of the results. Methods for interactive segmentation typically operate under one of two paradigms for user guidance: (1) Specification of pieces of the boundary of the desired object(s). (2) Specification of correct segmentation labels for a small subset of the image elements. These types of user input are referred to as boundary constraints and regional constraints, respectively. This thesis concerns the development of methods for interactive segmentation, using a graph-theoretic approach. We view an image as an edge weighted graph, whose vertex set is the set of image elements, and whose edges are given by an adjacency relation among the image elements. Due to its discrete nature and mathematical simplicity, this graph based image representation lends itself well to the development of efficient, and provably correct, methods. The contributions in this thesis may be summarized as follows: Existing graph-based methods for interactive segmentation are modified to improve their performance on images with noisy or missing data, while maintaining a low computational cost. Fuzzy techniques are utilized to obtain segmentations from which feature measurements can be made with increased precision. A new paradigm for user guidance, that unifies and generalizes regional and boundary constraints, is proposed. The practical utility of the proposed methods is illustrated with examples from the medical field

Evaluation and control of inventory distribution systems with quantity based shipment consolidation

Joint consideration of inventory and shipment decisions is an important aspect of obtaining economically and environmentally sustainable distribution systems. We consider this issue in the context of a one-warehouse-multiple-retailer inventory system with quantity-based shipment consolidation to groups of nonidentical retailers facing Poisson demand. The system is centralized, with free information sharing and access to real-time point of sale data. Thus, demand information at the retailers is immediately conveyed upstream to the warehouse without any fixed ordering costs. However, fixed costs associated with handling and transporting goods from the warehouse to the retailers are reflected in the shipment consolidation policy. Stock replenishments at the warehouse are made from an outside supplier/manufacturer according to an (R, Q) policy. For this system, we derive an exact recursive method for determining the inventory level distributions at the retailers. This allows us to evaluate the expected inventory and shipment costs, fill-rates, and transport emissions for the entire system. We also show how to optimize the system by providing bounds on the optimal shipment quantities and the warehouse reorder level

Momentumeffekten på den svenska marknaden : En studie om börstrender på Nasdaq Stockholm och Nasdaq First North

Den här studien undersöker momentum på den svenska marknaden under perioden januari 2010 till december 2018. Studien finner resultat att historiska vinnare fortsätter generera en positiv råavkastning medan historiska förlorare över samma period fortsätter att generera en negativ råavkastning. Resultaten är robusta även vid justering för storlek av bolagen. Momentum återfinns likväl hos små, medelstora, som stora bolag individuellt. Prövning av avkastningen visar att den inte kan förklaras genom Fama och Frenchs trefaktormodell utan samtliga strategier erhåller en positiv, signifikant avvikelseavkastning. Studien visar också att momentum återfinns till den grad att historiska vinnare på egen hand kan generera en riskjusterad avkastning som slår marknaden. Således presenterar studien resultat som tydligt indikerar ett momentum bland bolag på den svenska marknaden

Hållbarhetsredovisningens framtid Hur svenska företag kommunicerar sina hållbarhetsaktiviteter via sociala medier

Syfte : Syftet med denna studie var att fördjupa förståelsen av hur svenska företag kommunicerar sina hållbarhetsaktiviteter till sina intressenter via sociala medier. Metod : Vi har utfört manuella sökningar med utvalda nyckelord på Vattenfall AB:s och H & M Hennes & Mauritz AB: s (H&M) webbplatser och sociala medier, för att identifiera relevanta sökträffar. Vi har kategoriserat sökträffarna enligt två kommunikationsstrategier: självcentrerad envägskommunikation och interagerande tvåvägskommunikation. För att undersöka hur dessa företag kommunicerar, innehåller denna studie även en kvalitativ textanalys av utvalda facebookinlägg. Resultat : Den insamlade datan visade att den självcentrerade kommunikationsstrategin användes betydligt mer än den interagerande strategin. Datan visade, i enskilda fall, på en interagerande tvåvägskommunikation. Dessa var dock endast på H&M:s sociala medier. Slutsatsen är att H&M och Vattenfall AB inte fullt nyttjar de kommunikativa fördelarna som sociala medier möjliggör. Studiens bidrag och originalitet: H&M och Vattenfall AB är globala företag och båda har varit med på Global Fortune 500-listan de senaste fem åren. På grund av deras position inom sina branscher har de varit studieobjekt för tidigare forskning. Det har också gjorts studier om organisationers användning av sociala medier för kommunikation. Dock har ingen studie undersökt dessa företags användning av olika kommunikationsstrategier på sociala medier för att kommunicera sina hållbarhetsaktiviteter till sina intressenter

Using Cooperative Game Theory to Analyse Allocations of Costs Related to Connecting Renewable Energy to the Power Grid

Building new wind farms is an important part in the transition to renewable energy. However these projects often require large investments, and the cost of upgrading the existing infrastructure - to allow for the connection of new parks - is a component that cannot be ignored. When several wind farms seek interconnections, they are forced to collaborate and financing the connection. This leads to the question of how these costs should be shared between different agents. We investigate whether the currently used allocation method can and should be replaced with a fairer method, by formulating the problem as a cooperative game and using some well-established fairness axioms. Furthermore we apply our findings on the real case example Havsnäs wind farm in Sweden, as well as some fictive examples. Our findings show that in most cases, the current method where costs are divided proportionally to the total effect that the wind farm produces, is best suited. However, in some particular examples a more intricate mathematical method of cost sharing would be preferred

RayCaching : Amortized Isosurface Rendering for Virtual Reality

Real‐time virtual reality requires efficient rendering methods to deal with high‐ resolution stereoscopic displays and low latency head‐tracking. Our proposed RayCaching method renders isosurfaces of large volume datasets by amortizing raycasting over several frames and caching primary rays as small bricks that can be efficiently rasterized. An occupancy map in form of a clipmap provides level of detail and ensures that only bricks corresponding to visible points on the isosurface are being cached and rendered. Hard shadows and ambient occlusion from secondary rays are also accumulated and stored in the cache. Our method supports real‐time isosurface rendering with dynamic isovalue and allows stereoscopic visualization and exploration of large volume datasets at framerates suitable for virtual reality applications