EWA Splatting

In this paper, we present a framework for high quality splatting based on elliptical Gaussian kernels. To avoid aliasing artifacts, we introduce the concept of a resampling filter, combining a reconstruction kernel with a low-pass filter. Because of the similarity to Heckbert's EWA (elliptical weighted average) filter for texture mapping, we call our technique EWA splatting. Our framework allows us to derive EWA splat primitives for volume data and for point-sampled surface data. It provides high image quality without aliasing artifacts or excessive blurring for volume data and, additionally, features anisotropic texture filtering for point-sampled surfaces. It also handles nonspherical volume kernels efficiently; hence, it is suitable for regular, rectilinear, and irregular volume datasets. Moreover, our framework introduces a novel approach to compute the footprint function, facilitating efficient perspective projection of arbitrary elliptical kernels at very little additional cost. Finally, we show that EWA volume reconstruction kernels can be reduced to surface reconstruction kernels. This makes our splat primitive universal in rendering surface and volume data.Engineering and Applied Science

A method for viewing and interacting with medical volumes in virtual reality

The medical field has long benefited from advancements in diagnostic imaging technology. Medical images created through methods such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are used by medical professionals to non-intrusively peer into the body to make decisions about surgeries. Over time, the viewing medium of medical images has evolved from X-ray film negatives to stereoscopic 3D displays, with each new development enhancing the viewer’s ability to discern detail or decreasing the time needed to produce and render a body scan. Though doctors and surgeons are trained to view medical images in 2D, some are choosing to view body scans in 3D through volume rendering. While traditional 2D displays can be used to display 3D data, a viewing method that incorporates depth would convey more information to the viewer. One device that has shown promise in medical image viewing applications is the Virtual Reality Head Mounted Display (VR HMD). VR HMDs have recently increased in popularity, with several commodity devices being released within the last few years. The Oculus Rift, HTC Vive, and Windows Mixed Reality HMDs like the Samsung Odyssey offer higher resolution screens, more accurate motion tracking, and lower prices than earlier HMDs. They also include motion-tracked handheld controllers meant for navigation and interaction in video games. Because of their popularity and low cost, medical volume viewing software that is compatible with these headsets would be accessible to a wide audience. However, the introduction of VR to medical volume rendering presents difficulties in implementing consistent user interactions and ensuring performance. Though all three headsets require unique driver software, they are compatible with OpenVR, a middleware that standardizes communication between the HMD, the HMD’s controllers, and VR software. However, the controllers included with the HMDs each has a slightly different control layout. Furthermore, buttons, triggers, touchpads, and joysticks that share the same hand position between devices do not report values to OpenVR in the same way. Implementing volume rendering functions like clipping and tissue density windowing on VR controllers could improve the user’s experience over mouse-and-keyboard schemes through the use of tracked hand and finger movements. To create a control scheme that is compatible with multiple HMD’s A way of mapping controls differently depending on the device was developed. Additionally, volume rendering is a computationally intensive process, and even more so when rendering for an HMD. By using techniques like GPU raytracing with modern GPUs, real-time framerates are achievable on desktop computers with traditional displays. However, the importance of achieving high framerates is even greater when viewing with a VR HMD due to its higher level of immersion. Because the 3D scene occupies most of the user’s field of view, low or choppy framerates contribute to feelings of motion sickness. This was mitigated through a decrease in volume rendering quality in situations where the framerate drops below acceptable levels. The volume rendering and VR interaction methods described in this thesis were demonstrated in an application developed for immersive viewing of medical volumes. This application places the user and a medical volume in a 3D VR environment, allowing the user to manually place clipping planes, adjust the tissue density window, and move the volume to achieve different viewing angles with handheld motion tracked controllers. The result shows that GPU raytraced medical volumes can be viewed and interacted with in VR using commodity hardware, and that a control scheme can be mapped to allow the same functions on different HMD controllers despite differences in layout

Splatting multiresolution volume data using the feature graph

We propose to represent classified datasets as a feature graph storing different graphical models and attributes for each feature. This graph allows us to render each feature according to its own characteristics. In addition, we show that various features of the graph storing volume information at different resolution levels can be rendered together using a view-aligned splatting method. Moreover, we propose a 2D kernel function for splats that is easy to tune and generates smaller footprints that reduce the render time. Our algorithm provides images with less blur. It enhances the boundary of the features while avoiding the subdivision of homogeneous regions of the volume.Postprint (published version

Image-space sheet-buffered splatting on the GPU

Image-Space Sheet-Buffered Splatting is a popular high quality volume-rendering technique specially suitable for zoomed views of the data. On the contrary to other splatting approaches, it processes the voxels in slabs perpendicular to the viewing direction. Recently, a GPU design of this method has been proposed that considerably accelerates the rendering stage. However, the bottleneck of the method is the computation of the buckets, i.e the structure handling the voxels to be rendered in each slab. This stage of the method is done on the CPU. In this paper, we propose a new design of the method that creates and manages the buckets on the GPU. The proposed method is more than twice faster than the previous ones.Postprint (published version

Stereoscopic Sketchpad: 3D Digital Ink

--Context-- This project looked at the development of a stereoscopic 3D environment in which a user is able to draw freely in all three dimensions. The main focus was on the storage and manipulation of the ‘digital ink’ with which the user draws. For a drawing and sketching package to be effective it must not only have an easy to use user interface, it must be able to handle all input data quickly and efficiently so that the user is able to focus fully on their drawing. --Background-- When it comes to sketching in three dimensions the majority of applications currently available rely on vector based drawing methods. This is primarily because the applications are designed to take a users two dimensional input and transform this into a three dimensional model. Having the sketch represented as vectors makes it simpler for the program to act upon its geometry and thus convert it to a model. There are a number of methods to achieve this aim including Gesture Based Modelling, Reconstruction and Blobby Inflation. Other vector based applications focus on the creation of curves allowing the user to draw within or on existing 3D models. They also allow the user to create wire frame type models. These stroke based applications bring the user closer to traditional sketching rather than the more structured modelling methods detailed. While at present the field is inundated with vector based applications mainly focused upon sketch-based modelling there are significantly less voxel based applications. The majority of these applications focus on the deformation and sculpting of voxmaps, almost the opposite of drawing and sketching, and the creation of three dimensional voxmaps from standard two dimensional pixmaps. How to actually sketch freely within a scene represented by a voxmap has rarely been explored. This comes as a surprise when so many of the standard 2D drawing programs in use today are pixel based. --Method-- As part of this project a simple three dimensional drawing program was designed and implemented using C and C++. This tool is known as Sketch3D and was created using a Model View Controller (MVC) architecture. Due to the modular nature of Sketch3Ds system architecture it is possible to plug a range of different data structures into the program to represent the ink in a variety of ways. A series of data structures have been implemented and were tested for efficiency. These structures were a simple list, a 3D array, and an octree. They have been tested for: the time it takes to insert or remove points from the structure; how easy it is to manipulate points once they are stored; and also how the number of points stored effects the draw and rendering times. One of the key issues brought up by this project was devising a means by which a user is able to draw in three dimensions while using only two dimensional input devices. The method settled upon and implemented involves using the mouse or a digital pen to sketch as one would in a standard 2D drawing package but also linking the up and down keyboard keys to the current depth. This allows the user to move in and out of the scene as they draw. A couple of user interface tools were also developed to assist the user. A 3D cursor was implemented and also a toggle, which when on, highlights all of the points intersecting the depth plane on which the cursor currently resides. These tools allow the user to see exactly where they are drawing in relation to previously drawn lines. --Results-- The tests conducted on the data structures clearly revealed that the octree was the most effective data structure. While not the most efficient in every area, it manages to avoid the major pitfalls of the other structures. The list was extremely quick to render and draw to the screen but suffered severely when it comes to finding and manipulating points already stored. In contrast the three dimensional array was able to erase or manipulate points effectively while the draw time rendered the structure effectively useless, taking huge amounts of time to draw each frame. The focus of this research was on how a 3D sketching package would go about storing and accessing the digital ink. This is just a basis for further research in this area and many issues touched upon in this paper will require a more in depth analysis. The primary area of this future research would be the creation of an effective user interface and the introduction of regular sketching package features such as the saving and loading of images

Efficient automatic correction and segmentation based 3D visualization of magnetic resonance images

In the recent years, the demand for automated processing techniques for digital medical image volumes has increased substantially. Existing algorithms, however, still often require manual interaction, and newly developed automated techniques are often intended for a narrow segment of processing needs. The goal of this research was to develop algorithms suitable for fast and effective correction and advanced visualization of digital MR image volumes with minimal human operator interaction. This research has resulted in a number of techniques for automated processing of MR image volumes, including a novel MR inhomogeneity correction algorithm derivative surface fitting (dsf), automatic tissue detection algorithm (atd), and a new fast technique for interactive 3D visualization of segmented volumes called gravitational shading (gs). These newly developed algorithms provided a foundation for the automated MR processing pipeline incorporated into the UniViewer medical imaging software developed in our group and available to the public. This allowed the extensive testing and evaluation of the proposed techniques. Dsf was compared with two previously published methods on 17 digital image volumes. Dsf demonstrated faster correction speeds and uniform image quality improvement in this comparison. Dsf was the only algorithm that did not remove anatomic detail. Gs was compared with the previously published algorithm fsvr and produced rendering quality improvement while preserving real-time frame-rates. These results show that the automated pipeline design principles used in this dissertation provide necessary tools for development of a fast and effective system for the automated correction and visualization of digital MR image volumes

Volumetric cloud generation using a Chinese brush calligraphy style

Includes bibliographical references.Clouds are an important feature of any real or simulated environment in which the sky is visible. Their amorphous, ever-changing and illuminated features make the sky vivid and beautiful. However, these features increase both the complexity of real time rendering and modelling. It is difficult to design and build volumetric clouds in an easy and intuitive way, particularly if the interface is intended for artists rather than programmers. We propose a novel modelling system motivated by an ancient painting style, Chinese Landscape Painting, to address this problem. With the use of only one brush and one colour, an artist can paint a vivid and detailed landscape efficiently. In this research, we develop three emulations of a Chinese brush: a skeleton-based brush, a 2D texture footprint and a dynamic 3D footprint, all driven by the motion and pressure of a stylus pen. We propose a hybrid mapping to generate both the body and surface of volumetric clouds from the brush footprints. Our interface integrates these components along with 3D canvas control and GPU-based volumetric rendering into an interactive cloud modelling system. Our cloud modelling system is able to create various types of clouds occurring in nature. User tests indicate that our brush calligraphy approach is preferred to conventional volumetric cloud modelling and that it produces convincing 3D cloud formations in an intuitive and interactive fashion. While traditional modelling systems focus on surface generation of 3D objects, our brush calligraphy technique constructs the interior structure. This forms the basis of a new modelling style for objects with amorphous shape

Dynamic Volume Rendering of Functional Medical Data on Dissimilar Hardware Platforms

In the last 30 years, medical imaging has become one of the most used diagnostic tools in the medical profession. Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) technologies have become widely adopted because of their ability to capture the human body in a non-invasive manner. A volumetric dataset is a series of orthogonal 2D slices captured at a regular interval, typically along the axis of the body from the head to the feet. Volume rendering is a computer graphics technique that allows volumetric data to be visualized and manipulated as a single 3D object. Iso-surface rendering, image splatting, shear warp, texture slicing, and raycasting are volume rendering methods, each with associated advantages and disadvantages. Raycasting is widely regarded as the highest quality renderer of these methods. Originally, CT and MRI hardware was limited to providing a single 3D scan of the human body. The technology has improved to allow a set of scans capable of capturing anatomical movements like a beating heart. The capturing of anatomical data over time is referred to as functional imaging. Functional MRI (fMRI) is used to capture changes in the human body over time. While fMRI’s can be used to capture any anatomical data over time, one of the more common uses of fMRI is to capture brain activity. The fMRI scanning process is typically broken up into a time consuming high resolution anatomical scan and a series of quick low resolution scans capturing activity. The low resolution activity data is mapped onto the high resolution anatomical data to show changes over time. Academic research has advanced volume rendering and specifically fMRI volume rendering. Unfortunately, academic research is typically a one-off solution to a singular medical case or set of data, causing any advances to be problem specific as opposed to a general capability. Additionally, academic volume renderers are often designed to work on a specific device and operating system under controlled conditions. This prevents volume rendering from being used across the ever expanding number of different computing devices, such as desktops, laptops, immersive virtual reality systems, and mobile computers like phones or tablets. This research will investigate the feasibility of creating a generic software capability to perform real-time 4D volume rendering, via raycasting, on desktop, mobile, and immersive virtual reality platforms. Implementing a GPU-based 4D volume raycasting method for mobile devices will harness the power of the increasing number of mobile computational devices being used by medical professionals. Developing support for immersive virtual reality can enhance medical professionals’ interpretation of 3D physiology with the additional depth information provided by stereoscopic 3D. The results of this research will help expand the use of 4D volume rendering beyond the traditional desktop computer in the medical field. Developing the same 4D volume rendering capabilities across dissimilar platforms has many challenges. Each platform relies on their own coding languages, libraries, and hardware support. There are tradeoffs between using languages and libraries native to each platform and using a generic cross-platform system, such as a game engine. Native libraries will generally be more efficient during application run-time, but they require different coding implementations for each platform. The decision was made to use platform native languages and libraries in this research, whenever practical, in an attempt to achieve the best possible frame rates. 4D volume raycasting provides unique challenges independent of the platform. Specifically, fMRI data loading, volume animation, and multiple volume rendering. Additionally, real-time raycasting has never been successfully performed on a mobile device. Previous research relied on less computationally expensive methods, such as orthogonal texture slicing, to achieve real-time frame rates. These challenges will be addressed as the contributions of this research. The first contribution was exploring the feasibility of generic functional data input across desktop, mobile, and immersive virtual reality. To visualize 4D fMRI data it was necessary to build in the capability to read Neuroimaging Informatics Technology Initiative (NIfTI) files. The NIfTI format was designed to overcome limitations of 3D file formats like DICOM and store functional imagery with a single high-resolution anatomical scan and a set of low-resolution anatomical scans. Allowing input of the NIfTI binary data required creating custom C++ routines, as no object oriented APIs freely available for use existed. The NIfTI input code was built using C++ and the C++ Standard Library to be both light weight and cross-platform. Multi-volume rendering is another challenge of fMRI data visualization and a contribution of this work. fMRI data is typically broken into a single high-resolution anatomical volume and a series of low-resolution volumes that capture anatomical changes. Visualizing two volumes at the same time is known as multi-volume visualization. Therefore, the ability to correctly align and scale the volumes relative to each other was necessary. It was also necessary to develop a compositing method to combine data from both volumes into a single cohesive representation. Three prototype applications were built for the different platforms to test the feasibility of 4D volume raycasting. One each for desktop, mobile, and virtual reality. Although the backend implementations were required to be different between the three platforms, the raycasting functionality and features were identical. Therefore, the same fMRI dataset resulted in the same 3D visualization independent of the platform itself. Each platform uses the same NIfTI data loader and provides support for dataset coloring and windowing (tissue density manipulation). The fMRI data can be viewed changing over time by either animation through the time steps, like a movie, or using an interface slider to “scrub” through the different time steps of the data. The prototype applications data load times and frame rates were tested to determine if they achieved the real-time interaction goal. Real-time interaction was defined by achieving 10 frames per second (fps) or better, based on the work of Miller [1]. The desktop version was evaluated on a 2013 MacBook Pro running OS X 10.12 with a 2.6 GHz Intel Core i7 processor, 16 GB of RAM, and a NVIDIA GeForce GT 750M graphics card. The immersive application was tested in the C6 CAVE™, a 96 graphics node computer cluster comprised of NVIDIA Quadro 6000 graphics cards running Red Hat Enterprise Linux. The mobile application was evaluated on a 2016 9.7” iPad Pro running iOS 9.3.4. The iPad had a 64-bit Apple A9X dual core processor with 2 GB of built in memory. Two different fMRI brain activity datasets with different voxel resolutions were used as test datasets. Datasets were tested using both the 3D structural data, the 4D functional data, and a combination of the two. Frame rates for the desktop implementation were consistently above 10 fps, indicating that real-time 4D volume raycasting is possible on desktop hardware. The mobile and virtual reality platforms were able to perform real-time 3D volume raycasting consistently. This is a marked improvement for 3D mobile volume raycasting that was previously only able to achieve under one frame per second [2]. Both VR and mobile platforms were able to raycast the 4D only data at real-time frame rates, but did not consistently meet 10 fps when rendering both the 3D structural and 4D functional data simultaneously. However, 7 frames per second was the lowest frame rate recorded, indicating that hardware advances will allow consistent real-time raycasting of 4D fMRI data in the near future

Validating Stereoscopic Volume Rendering

The evaluation of stereoscopic displays for surface-based renderings is well established in terms of accurate depth perception and tasks that require an understanding of the spatial layout of the scene. In comparison direct volume rendering (DVR) that typically produces images with a high number of low opacity, overlapping features is only beginning to be critically studied on stereoscopic displays. The properties of the specific images and the choice of parameters for DVR algorithms make assessing the effectiveness of stereoscopic displays for DVR particularly challenging and as a result existing literature is sparse with inconclusive results. In this thesis stereoscopic volume rendering is analysed for tasks that require depth perception including: stereo-acuity tasks, spatial search tasks and observer preference ratings. The evaluations focus on aspects of the DVR rendering pipeline and assess how the parameters of volume resolution, reconstruction filter and transfer function may alter task performance and the perceived quality of the produced images. The results of the evaluations suggest that the transfer function and choice of recon- struction filter can have an effect on the performance on tasks with stereoscopic displays when all other parameters are kept consistent. Further, these were found to affect the sensitivity and bias response of the participants. The studies also show that properties of the reconstruction filters such as post-aliasing and smoothing do not correlate well with either task performance or quality ratings. Included in the contributions are guidelines and recommendations on the choice of pa- rameters for increased task performance and quality scores as well as image based methods of analysing stereoscopic DVR images