Mapping the spatiotemporal dynamics of calcium signaling in cellular neural networks using optical flow

An optical flow gradient algorithm was applied to spontaneously forming net- works of neurons and glia in culture imaged by fluorescence optical microscopy in order to map functional calcium signaling with single pixel resolution. Optical flow estimates the direction and speed of motion of objects in an image between subsequent frames in a recorded digital sequence of images (i.e. a movie). Computed vector field outputs by the algorithm were able to track the spatiotemporal dynamics of calcium signaling pat- terns. We begin by briefly reviewing the mathematics of the optical flow algorithm, and then describe how to solve for the displacement vectors and how to measure their reliability. We then compare computed flow vectors with manually estimated vectors for the progression of a calcium signal recorded from representative astrocyte cultures. Finally, we applied the algorithm to preparations of primary astrocytes and hippocampal neurons and to the rMC-1 Muller glial cell line in order to illustrate the capability of the algorithm for capturing different types of spatiotemporal calcium activity. We discuss the imaging requirements, parameter selection and threshold selection for reliable measurements, and offer perspectives on uses of the vector data.Comment: 23 pages, 5 figures. Peer reviewed accepted version in press in Annals of Biomedical Engineerin

GPUFLIC: interactive and accurate dense visualization of unsteady flows

Journal ArticleAbstract The paper presents an efficient and accurate implementation of Unsteady Flow LIC (UFLIC) on the Graphics Processing Unit (GPU). We obtain the same, high quality texture representation of unsteady two-dimensional flows as the original, time-consuming method but leverage the features of today's commodity hardware to achieve interactive frame rates. Despite a remarkable number of recent contributions in the field of texture-based visualization of time-dependent vector fields, the present paper is the first to provide a faithful implementation of that prominent technique fully supported by the graphics pipeline

ClimateNeRF: Physically-based Neural Rendering for Extreme Climate Synthesis

Physical simulations produce excellent predictions of weather effects. Neural radiance fields produce SOTA scene models. We describe a novel NeRF-editing procedure that can fuse physical simulations with NeRF models of scenes, producing realistic movies of physical phenomena inthose scenes. Our application -- Climate NeRF -- allows people to visualize what climate change outcomes will do to them. ClimateNeRF allows us to render realistic weather effects, including smog, snow, and flood. Results can be controlled with physically meaningful variables like water level. Qualitative and quantitative studies show that our simulated results are significantly more realistic than those from state-of-the-art 2D image editing and 3D NeRF stylization.Comment: project page: https://climatenerf.github.io

ANALYSIS AND VISUALIZATION OF FLOW FIELDS USING INFORMATION-THEORETIC TECHNIQUES AND GRAPH-BASED REPRESENTATIONS

Three-dimensional flow visualization plays an essential role in many areas of science and engineering, such as aero- and hydro-dynamical systems which dominate various physical and natural phenomena. For popular methods such as the streamline visualization to be effective, they should capture the underlying flow features while facilitating user observation and understanding of the flow field in a clear manner. My research mainly focuses on the analysis and visualization of flow fields using various techniques, e.g. information-theoretic techniques and graph-based representations. Since the streamline visualization is a popular technique in flow field visualization, how to select good streamlines to capture flow patterns and how to pick good viewpoints to observe flow fields become critical. We treat streamline selection and viewpoint selection as symmetric problems and solve them simultaneously using the dual information channel [81]. To the best of my knowledge, this is the first attempt in flow visualization to combine these two selection problems in a unified approach. This work selects streamline in a view-independent manner and the selected streamlines will not change for all viewpoints. My another work [56] uses an information-theoretic approach to evaluate the importance of each streamline under various sample viewpoints and presents a solution for view-dependent streamline selection that guarantees coherent streamline update when the view changes gradually. When projecting 3D streamlines to 2D images for viewing, occlusion and clutter become inevitable. To address this challenge, we design FlowGraph [57, 58], a novel compound graph representation that organizes field line clusters and spatiotemporal regions hierarchically for occlusion-free and controllable visual exploration. We enable observation and exploration of the relationships among field line clusters, spatiotemporal regions and their interconnection in the transformed space. Most viewpoint selection methods only consider the external viewpoints outside of the flow field. This will not convey a clear observation when the flow field is clutter on the boundary side. Therefore, we propose a new way to explore flow fields by selecting several internal viewpoints around the flow features inside of the flow field and then generating a B-Spline curve path traversing these viewpoints to provide users with closeup views of the flow field for detailed observation of hidden or occluded internal flow features [54]. This work is also extended to deal with unsteady flow fields. Besides flow field visualization, some other topics relevant to visualization also attract my attention. In iGraph [31], we leverage a distributed system along with a tiled display wall to provide users with high-resolution visual analytics of big image and text collections in real time. Developing pedagogical visualization tools forms my other research focus. Since most cryptography algorithms use sophisticated mathematics, it is difficult for beginners to understand both what the algorithm does and how the algorithm does that. Therefore, we develop a set of visualization tools to provide users with an intuitive way to learn and understand these algorithms

Visuelle Analyse großer Partikeldaten

Partikelsimulationen sind eine bewährte und weit verbreitete numerische Methode in der Forschung und Technik. Beispielsweise werden Partikelsimulationen zur Erforschung der Kraftstoffzerstäubung in Flugzeugturbinen eingesetzt. Auch die Entstehung des Universums wird durch die Simulation von dunkler Materiepartikeln untersucht. Die hierbei produzierten Datenmengen sind immens. So enthalten aktuelle Simulationen Billionen von Partikeln, die sich über die Zeit bewegen und miteinander interagieren. Die Visualisierung bietet ein großes Potenzial zur Exploration, Validation und Analyse wissenschaftlicher Datensätze sowie der zugrundeliegenden Modelle. Allerdings liegt der Fokus meist auf strukturierten Daten mit einer regulären Topologie. Im Gegensatz hierzu bewegen sich Partikel frei durch Raum und Zeit. Diese Betrachtungsweise ist aus der Physik als das lagrange Bezugssystem bekannt. Zwar können Partikel aus dem lagrangen in ein reguläres eulersches Bezugssystem, wie beispielsweise in ein uniformes Gitter, konvertiert werden. Dies ist bei einer großen Menge an Partikeln jedoch mit einem erheblichen Aufwand verbunden. Darüber hinaus führt diese Konversion meist zu einem Verlust der Präzision bei gleichzeitig erhöhtem Speicherverbrauch. Im Rahmen dieser Dissertation werde ich neue Visualisierungstechniken erforschen, welche speziell auf der lagrangen Sichtweise basieren. Diese ermöglichen eine effiziente und effektive visuelle Analyse großer Partikeldaten

혈관 구조 분석 기반 혈류선 추출과 불투명도 변조를 이용한 혈류 가시화 기법

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 2. 신영길.With recent advances in acquisition and simulation of blood flow data, blood flow visualization has been widely used in medical imaging for the diagnosis and treatment of pathological vessels. The integral line based method has been most commonly employed to depict hemodynamic data because it exhibits a long term flow behavior useful for flow analysis. This method generates integral lines to be used as a basis for graphical representation by tracing the trajectory of a massless particle released on the vector field through a numerical integration. However, there are several unsolved problems when this previous method is applied to thin curved vascular structures. The first one is to locate a seeding plane, which is manually performed in the existing methods, thus yielding inconsistent visual results. The second one is the early termination of a line integration due to locally reversed flow and narrow tubular structure, which results in short flowlines comparing with the vessel length. And the last one is the line occlusion caused by the dense depiction of flowlines. Additionally, in blood flow visualization for clinical uses, it is essential to apparently exhibit abnormal flow relevant to vessel diseases. In this paper, we present an enhanced method that overcomes problems related to the integration based flow visualization and depicts hemodynamics in a more informative way for assisting the diagnosis process. Using the fact that blood flow passes through the inlet or outlet but is blocked by vessel wall, we firstly identify the vessel inlet or outlet by the orthogonality metric between flow velocity vector and vessel surface normal vector. Then, we generate seed points on the detected inlet or outlet by Poisson disk sampling. Therefore, we can achieve the automatic seeding that leads to a consistent and faster flow depiction by skipping the manual location of a seeding plane to initiate the line integration. In addition, we resolve the early terminated line integration by applying the tracing direction adaptively based on flow direction at each seed point and by performing the additional seeding near the terminated location. This solution enables to yield length-extended flowlines, which contribute to faithful flow visualization. Based on the observation that blood flow usually follows the vessel track if there is no obstacle or leak in the middle of a passage, we define the representative flowline for each branch by the vessel centerline. Then, we render flowlines by assigning the opacity according to their shape similarity with the vessel centerline so that flowlines similar to the vessel centerline are shown transparently, while different ones opaquely. Accordingly, our opacity modulation method enables flowlines with unusual flow pattern to appear more noticeable, while minimizing visual clutter and line occlusion. Finally, we introduce HSV (hue, saturation, value) color coding to simultaneously exhibit flow attributes such as local speed and residence time. This color coding gives a more realistic fading effect on the older particles or line segments by attenuating the saturation according to the residence time. Hence, it supports users in comprehending intuitively multiple information at once. Experimental results show that our technique is well suitable to depict blood flow in vascular structures.Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Problem Statement 3 1.3 Main Contribtion 7 1.4 Organization of the Dissertation 8 Chapter 2 Related Works 9 2.1 Flow and Velocity Vector 9 2.2 Flow Visualization 10 2.3 Blood Flow Visualization 16 2.3.1 Geometric Method 16 2.3.2 Feature-Based Method 18 2.3.3 Partition-Based Method 19 Chapter 3 Integration based Flowline Extraction 22 3.1 Overview 22 3.2 Seeding 23 3.3 Barycentric Coordinate Conversion 24 3.4 Cell Searching 26 3.5 Velocity Vector Calculation 27 3.6 Advection 28 3.7 Step Size Adaptation 30 Chapter 4 Blood Flow Visualization using Flow and Geometric Analysis 32 4.1 Preprocessing 33 4.2 Inlet or Outlet based Seeding 35 4.3 Tracing 39 4.3.1 Flow based Bidirectional Tracing 39 4.3.2 Additional Seeding for Length Extended Line Integration 41 4.4 Opacity Modulation 43 4.4.1 Global Opacity 45 4.4.2 Local Opacity 46 4.4.3 Opacity Adjustment 52 4.4.4 Blending 53 4.5 HSV Color Coding 54 4.6 Vessel Rendering 58 4.6.1 Vessel Smoothing 59 4.6.2 Vessel Contour Enhancement 60 4.7 Flowline Drawing 61 4.7.1 Line Illumination 61 4.7.2 Line Halo 63 4.8 Animation 64 Chapter 5 Experimental Results 67 5.1 Evaluation on Seeding 69 5.2 Evaluation on Tracing 74 5.3 Evaluation on Opacity Modulation 82 5.4 Parameter Study 85 Chapter 6 Conclusion 87 Bibliography 89 초 록 99Docto