Linköping studies in science and technology. Dissertation, No PDF

Linköping studies in science and technology. Dissertation, No ENHANCING SALIENT FEATURES IN VOLUMETRIC DATA USING ILLUMINATION AND TRANSFER FUNCTIONS Daniel Jönsson Division of Media and Information

Please download to get full document.

View again

of 63
All materials on our website are shared by users. If you have any questions about copyright issues, please report us to resolve them. We are always happy to assist you.


Publish on:

Views: 45 | Pages: 63

Extension: PDF | Download: 0

Linköping studies in science and technology. Dissertation, No ENHANCING SALIENT FEATURES IN VOLUMETRIC DATA USING ILLUMINATION AND TRANSFER FUNCTIONS Daniel Jönsson Division of Media and Information Technology Department of Science and Technology Linköping University, SE Norrköping, Sweden Norrköping, October 2016 Enhancing Salient Features in Volumetric Data Using Illumination and Transfer Functions Copyright 2016 Daniel Jönsson (unless otherwise noted) Division of Media and Information Technology Department of Science and Technology Campus Norrköping, Linköping University SE Norrköping, Sweden ISBN: ISSN: Printed in Sweden by LiU-Tryck, Linköping, 2016 Acknowledgments The work resulting in this thesis would not have been possible without my enthusiastic and incredibly smart supervisors, colleagues and co-authors. Hours of interesting discussions have been spent over coffee and many whiteboards have been filled during those discussions. I would like to express my sincere gratitude to my supervisor Anders Ynnerman who has provided guidance and inspiration. Thanks also goes to my co-supervisors Timo Ropinski and Patric Ljung. Timo was my co-supervisor during my first years as a PhD and was very supportive and helpful during those initial confusing years. Patric took over the role as co-supervisor during the last time and has acted as an excellent sounding board. Colleagues with whom work and non-work related discussions have been made include Alexander Bock, who is the kindest metal fan I know, Andrew Gardner who always has a fist bump at hand, Erik Sundén who I would like to thank for applying the VIS-police approval approach on the papers, Joel Kronander who is bringing a theoretic point of view into the discussions, Martin Falk who has provided both climbing and paper experiences, Peter Steneteg who has contributed with his programming mastermind, Rickard Englund who may be the secret chancellor?, Sathish Kotravel who has an amazing ability to come up with one-liners, Stefan Lindholm with whom I had thorough discussions on the discreteness of nature and Tan Khoa Nguen who taught me how a proper bribing of a Vietnamese border control officer should be done. Our administrator Eva Skärblom deserves a special thanks for her immaculate work. I would also like to thank the Center of Medical Imaging and Visualization (CMIV) for providing interesting data to visualize. I have also had the opportunity to work together with Isabelle Wegmann Hachette and Gunnar Läthen at Context Vision AB, Claes Lundström at Sectra AB and Katarina Sperling at the Norrköping Visualization Center. These companies show that my work as a PhD student extend beyond the published papers. Several people have proofread this work and made comments that significantly improved it. Thank you Martin Falk, Andrew Gardner, Joel Kronander, Erik Sundén and Anders Ynnerman. This work would not have been possible without funding agencies. Many thanks to the Swedish e-science Research Centre (SeRC), the Swedish Research Council (VR), the Knut and Alice Wallenberg Foundation (KAW) and the Excellence Center at Linköping and Lund in Information Technology (ELLIIT). I am also grateful for the time spent abroad in Vancouver together with Torsten Möller and collaborations with the people at the SCI institute in Salt Lake City, especially Tiago Etiene. Finally, I would like to thank my family for illuminating my time out-of-office, 3 Malin and Edvin! v Abstract The visualization of volume data is a fundamental component in the medical domain. Volume data is used in the clinical work-flow to diagnose patients and is therefore of uttermost importance. The amount of data is rapidly increasing as sensors, such as computed tomography scanners, become capable of measuring more details and gathering more data over time. Unfortunately, the increasing amount of data makes it computationally challenging to interactively apply high quality methods to increase shape and depth perception. Furthermore, methods for exploring volume data has mostly been designed for experts, which prohibits novice users from exploring volume data. This thesis aims to address these challenges by introducing efficient methods for enhancing salient features through high quality illumination as well as methods for intuitive volume data exploration. Humans are interpreting the world around them by observing how light interacts with objects. Shadows enable us to better determine distances while shifts in color enable us to better distinguish objects and identify their shape. These concepts are also applicable to computer generated content. The perception in volume data visualization can therefore be improved by simulating real-world light interaction. However, realistic light simulation is a computationally challenging problem. This thesis presents efficient methods that are capable of interactively simulating realistic light propagation in volume data. In particular, this work shows how a multi-resolution grid can be used to encode the attenuation of light from all directions using spherical harmonics and thereby enable advanced interactive dynamic light configurations. Two methods are also presented that allow photon mapping calculations to be focused on visually changing areas. The results demonstrate that photon mapping can be used in interactive volume visualization for both static and time-varying volume data. Efficient and intuitive exploration of volume data requires methods that are easy to use and reflect the objects that were measured. A value that has been collected by a sensor commonly represents the material existing within a small neighborhood around a location. Recreating the original materials is difficult since the value represents a mixture of them. This is referred to as the partial-volume problem. A method is presented that derives knowledge from the user in order to reconstruct the original materials in a way which is more in line with what the user would expect. Sharp boundaries are visualized where the certainty is high while uncertain areas are visualized with fuzzy boundaries. The volume exploration process of mapping data values to optical properties through the transfer function has traditionally been complex and performed by expert users. In this thesis, a dynamic gallery of the data is combined with touch interaction to allow novice users to explore volume data. A study at a science center showed that visitors favor the presented dynamic gallery method compared to the most commonly used transfer function editor. vii Populärvetenskaplig Sammanfattning Medicinska verktyg som till exempel datortomografskanners kan idag samla in tusentals bilder av kroppens inre och tillsammans formar de en volym av data. Visualisering av volymdata är idag en grundläggande komponent i det kliniska arbetsflödet där det används för att ställa diagnoser på patienter. Visualiseringen gör att radiologer kan se inre organ och är därför ett viktigt verktyg i det kliniska arbetsflödet. Mängden information ökar kraftigt i takt med att skanners förbättrar sin detaljrikedom och förmåga att samla in information över tid. Den ökade detaljrikedomen gör att rätt diagnoser kan ställas med större säkerhet medan information över tid gör det möjligt att analysera organens funktion i kroppen. Det är en stor utmaning att hantera den ökande mängden volymdata och förbättra möjligheterna för användare att tolka informationen. Den här avhandlingen introducerar därför effektiva metoder för att framhäva viktiga delar i datan genom virtuell belysning samt metoder för att förenkla utforskningen av datan. Människor har sedan födseln tränats i att tolka världen omkring oss genom att observera hur ljus interagerar med objekt i vår omgivning. Skuggor gör att vi kan bedöma avstånd bättre medans färgskiftningar gör att vi kan separera objekt och bedöma dess form. Visualisering av volymdata kan därför förbättras genom att introducera en realistisk belysningsmiljö där vi kan använda vårt synsinne fullt ut för att tolka informationen. Realistisk ljussimulering kräver dock stora mängder beräkningar vilket hindrar den från att användas vid interaktiv visualisering. Det krävs därmed effektiva metoder för att interaktivt kunna simulera realistiskt ljus i volymdata. I den här avhandlingen visas hur avancerade dynamiska ljuskonfigurationer interaktivt kan simuleras. Ljussimulering av högre kvalité kan uppnås genom att representera ljuset med små energipartiklar kallade fotoner. Att använda fotoner för ljussättning i volymdata är beräkningstungt och har därför inte kunnat göras interaktivt tidigare. Två metoder presenteras som fokuserar beräkningarna på områden som förändras under utforskningen vilket gör att mängden beräkningar som behöver utföras kan reduceras. Resultaten visar att realistisk ljussimulering med fotoner därmed kan användas vid interaktiv visualisering av volymdata. För att uppnå effektiv och intuitiv utforskning av volymdata krävs metoder som är enkla att använda och återspeglar objekten som mäts. Ett mätvärde som har samlats in av en skanner representerar samtliga objekt inom ett visst område. Att återskapa objekten inom området är svårt eftersom mätvärdet representerar en blandning av objekten. I avhandlingen presenteras en metod som härleder kunskap från användaren för att återskapa objekten på ett sätt som ligger mer i linje med vad användaren förväntar sig. Gränser där objekten kan bestämmas med hög säkerhet återskapas som skarpa medan områden där osäkerheten är hög blir suddiga. Utforskning av volymdata har traditionellt varit en komplex process utförd av experter. Ett dynamiskt bildgalleri av volymdatan kombineras med ix x pekskärmsinteraktion för att oerfarna användare ska kunna utforska datan. En studie på ett museum visade att fler besökare föredrog det föreslagna dynamiska bildgalleriet jämfört den vanligaste metoden för att utforska volymdata. Metoderna presenterade i den här avhandlingen är främst demonstrerade på medicinsk data men de kan också appliceras på volymdata från andra områden. Publications The following publications are included in this dissertation: Paper A: D. Jönsson, E. Sundén, A. Ynnerman, and T. Ropinski. A Survey of Volumetric Illumination Techniques for Interactive Volume Rendering. Computer Graphics Forum, 33(1):27 51, 2014 Paper B: J. Kronander, D. Jönsson, J. Löw, P. Ljung, A. Ynnerman, and J. Unger. Efficient Visibility Encoding for Dynamic Illumination in Direct Volume Rendering. IEEE Transactions on Visualization and Computer Graphics, 18(3): , 2012 Paper C: D. Jönsson, J. Kronander, T. Ropinski, and A. Ynnerman. Historygrams: Enabling Interactive Global Illumination in Direct Volume Rendering Using Photon Mapping. IEEE Transactions on Visualization and Computer Graphics, 18(12): , 2012 Paper D: D. Jönsson and A. Ynnerman. Correlated Photon Mapping for Interactive Global Illumination of Time-Varying Volumetric Data. IEEE Transactions on Visualization and Computer Graphics, 23, 2017, in press Paper E: S. Lindholm, D. Jönsson, C. Hansen, and A. Ynnerman. Boundary Aware Reconstruction of Scalar Fields. IEEE Transactions on Visualization and Computer Graphics, 20(12): , 2014 Paper F: D. Jönsson, M. Falk, and A. Ynnerman. Intuitive Exploration of Volumetric Data Using Dynamic Galleries. IEEE Transactions on Visualization and Computer Graphics, 22(1): , 2016 xi xii The following publications, listed in reverse chronological order, have been published in relation to the work performed during the thesis but are not included in the dissertation: D. Jönsson, E. Sundén, G. Läthén, and I. W. Hachette. Method and System for Volume Rendering of Medical Images, patent pending [Online]. Available: Accessed: E. Sundén, A. Bock, D. Jönsson, A. Ynnerman, and T. Ropinski. Interaction Techniques as a Communication Channel when Presenting 3D Visualizations. In IEEE VIS International Workshop on 3DVis, pages 2 6, 2014 J. Parulek, D. Jönsson, T. Ropinski, S. Bruckner, A. Ynnerman, and I. Viola. Continuous Levels-of-Detail and Visual Abstraction for Seamless Molecular Visualization. Computer Graphics Forum, 33(6): , 2014 J. Kronander, J. Dahlin, D. Jönsson, M. Kok, T. Schön, and J. Unger. Real-Time Video Based Lighting Using GPU Raytracing. In European Signal Processing Conference (EUSIPCO 2014), pages , 2014 T. Etiene, D. Jönsson, T. Ropinski, C. Scheidegger, J. L. D. Comba, L. G. Nonato, R. M. Kirby, A. Ynnerman, and C. T. Silva. Verifying Volume Rendering using Discretization Error Analysis. IEEE Transactions on Visualization and Computer Graphics, 20(1): , 2014 S. Lindholm, D. Jönsson, H. Knutsson, and A. Ynnerman. Towards Data Centric Sampling for Volume Rendering. In SIGRAD, pages 55 60, 2013 N. Rostamzadeh, D. Jönsson, and T. Ropinski. Comparison of Volumetric Illumination Methods by Considering the Underlying Optical Models. In SIGRAD, pages 35 40, 2013 D. Jönsson, E. Sundén, A. Ynnerman, and T. Ropinski. State of The Art Report on Interactive Volume Rendering with Volumetric Illumination. In EG - State of the Art Reports, volume 1, pages 53 74, 2012 D. Jönsson, P. Ganestam, M. Doggett, A. Ynnerman, and T. Ropinski. Explicit Cache Management for Volume Ray-Casting on Parallel Architectures. In Eurographics Symposium on Parallel Graphics and Visualization, pages 31 40, 2012 Contributions Paper A: A Survey of Volumetric Illumination Techniques for Interactive Volume Rendering Presents an overview of the state-of-the art within the field of volumetric illumination. Methods within the field are compared with respect to their memory consumption, computational load and capabilities of producing high fidelity illumination when changing the transfer function, light sources or camera. Paper B: Efficient Visibility Encoding for Dynamic Illumination in Direct Volume Rendering Proposes the use of an efficient data structure to store and compute local and global visibility within the data set using spherical harmonics. The computational gain enables complex dynamic light setups to be used within interactive volume visualization. As a second author I was primarily involved in both the development and implementation of the method. The method was presented at the IEEE VIS TVCG track. Paper C: Historygrams: Enabling Interactive Global Illumination in Direct Volume Rendering Using Photon Mapping Introduces a representation of the data history of a photon and view ray that can be efficiently queried and stored. The data history is used to determine whether a photon or view ray is affected by a parameter change and therefore needs to be recomputed. The method increases the performance of the high fidelity photon mapping illumination technique such that it can be used for interactive volume exploration using the transfer function. The method was presented at IEEE VIS (SciVis). Paper D: Correlated Photon Mapping for Interactive Global Illumination of Time- Varying Volumetric Data Utilizes correlation between time-steps in volumetric data to determine and prioritize the subset of photons that need to be updated due to changes. A visual importance function is proposed that takes the data into account as well as the transfer function in order to determine the correlation of visible content between time steps. An approximate photon gathering approach is presented, which allows xiii xiv the photon density to be retrieved during camera movements using hardware accelerated filtering. The method advances the state-of-the-art performance in volumetric photon mapping such that it can be used for interactive volume exploration of time-varying volumetric data. The method received an honorable mention and is to be presented at IEEE VIS (SciVis). Paper E: Boundary Aware Reconstruction of Scalar Fields Improves the visualization of features in transition areas and at discontinuous material boundaries using encoded domain knowledge. The domain knowledge is supplied through a material classification and combined with the visual classification to reconstruct values that are more in line with the user s understanding of the nature of the data. The results show that visualizations which capture the nature of the data can be created with decreased interaction complexity compared to previous work. As a second author I was involved in developing the idea, the method and writing the manuscript. The method was presented at IEEE VIS (SciVis). Paper F: Intuitive Exploration of Volumetric Data Using Dynamic Galleries Makes volume data exploration for novice users easier through the use of dynamically generated gallery images of the data set. Each gallery image displays a sub-range of the data set s value range. Zooming and panning is used to change the displayed data value range, causing the gallery to dynamically update, and enables the user to get both an overview as well as details on demand. A user study showed that the presented method was preferred compared to a traditional approach without gallery images. The method was presented at IEEE VIS (SciVis). Contents Acknowledgments Abstract Populärvetenskaplig Sammanfattning List of publications Contributions v vii ix xi xiii 1 Motivation Visual analysis of complex information Enhancing salient features Visualizing volume data 3 2 Introduction The visualization pipeline Static volume data Time-varying volume data Volume data generation Volume data visualization Direct volume rendering Transfer functions One-dimensional transfer functions Multi-dimensional transfer functions 12 3 Selected challenges in volume data exploration Background Light transport theory for volumetric data Material scattering Solving the light transport equation Enhancing salient features using illumination Spherical harmonics encoding Photon mapping Illumination of time-varying volumetric data Summary of challenges in volumetric illumination Data exploration using the transfer function Feature separation Feature reconstruction Interaction complexity 26 xv Contents Summary of challenges in transfer function interaction 27 4 Enhancing and exploring salient features (contributions) Overview Unconstrained volume illumination Dynamic light sources Dynamic transfer function Dynamic volume data Reconstructing what the user wants Feature-based reconstruction Dealing with the partial volume effect Volume data exploration for novice users Spatial connection for intuitive understanding Improving intuitiveness 45 5 Concluding remarks Interactive volumetric illumination Volumetric data exploration Outlook 51 Bibliography 55 Paper A 65 Paper B 95 Paper C 111 Paper D 123 Paper E 137 Paper F 149 xvi Chapter 1 Motivation A human is trained from the moment it is born to interpret the world through the visual sense. We are therefore remarkably good at forming a mental image of the information that is fed through our eyes. Examples from the Gestalt principles in Figure 1.1 demonstrate how quickly and easy we understand information through the visual sense [1]. We can identify groups depending on how close features are to each other and fill in missing information without consciously thinking about it [74]. Providing visual representations of complex information is therefore increasingly important to allow humans to understand and reason about the large amounts of information available today. (a) Proximity (b) Closure Figure 1.1: Examples of human interpretation capabilities given by the Gestalt principles. (a) Objects perceived close to each other form groups. (b) Objects are perceived as whole even though they are incomplete. 2 Chapter 1 Motivation (a) Single image (b) Several images (c) Organized images Figure 1.2: We can quickly understand the contents of a single image (a). But it takes more time to understand the relation between images whe
Related Search
We Need Your Support
Thank you for visiting our website and your interest in our free products and services. We are nonprofit website to share and download documents. To the running of this website, we need your help to support us.

Thanks to everyone for your continued support.

No, Thanks