Image-space Algorithm Research Articles

Performance of Iterative Reconstruction in Image Space Algorithm in Combination with Automatic Tube Current Modulation Compared to Filtered Back Projection in Brain CT Scan.

High-quality images with minimum radiation dose are considered a challenge in Computed Tomography (CT) scans. The current study aimed to assess the efficacy of the Iterative Reconstruction in Image Space (IRIS) algorithm combined with Automatic Tube Current Modulation (ATCM) compared to Filtered Back Projection (FBP) in brain CT scans. In this cross-sectional study, 200 patients underwent to brain CT scan, and images were then reconstructed using both FBP and IRIS. The CT Number (CTN), noise, and Signal-to-Noise Ratio (SNR) were computed for different tissues from CT images. The performance of two algorithms under different exposure conditions was evaluated using a water phantom. Two experienced radiologists assessed the image quality. Volume CT Dose Index (CTDIvol) and Dose Length Product (DLP) were recorded for each scan. FBP reconstruction exhibited higher noise and lower SNR compared to IRIS, both with and without ATCM. Noise levels significantly increased for FBP combined with ATCM. Subjective analysis showed higher performance for IRIS without ATCM compared to other approaches. The mean CTDIvol with and without ATCM was 20.04±3.33 and 36.37±4.65 mGy, respectively. In the phantom study, the noise with IRIS remained lower than that with FBP even with a 42% dose reduction. IRIS algorithm can preserve the image quality when radiation dose is significantly reduced by ATCM in brain CT scan. Implementation of IRIS combined with ATCM is recommended for brain CT examinations.

Interactive Subsurface Scattering for Materials With High Scattering Distances

AbstractExisting algorithms for rendering subsurface scattering in real time cannot deal well with scattering over longer distances. Kernels for image space algorithms become very large in these circumstances and separation does not work anymore, while geometry‐based algorithms cannot preserve details very well. We present a novel approach that deals with all these downsides. While for lower scattering distances, the advantages of geometry‐based methods are small, this is not the case anymore for high scattering distances (as we will show). Our proposed method takes advantage of the highly detailed results of image space algorithms and combines it with a geometry‐based method to add the essential scattering from sources not included in image space. Our algorithm does not require pre‐computation based on the scene's geometry, it can be applied to static and animated objects directly. Our method is able to provide results that come close to ray‐traced images which we will show in direct comparisons with images generated by PBRT. We will compare our results to state of the art techniques that are applicable in these scenarios and will show that we provide superior image quality while maintaining interactive rendering times.

Density-based label placement

We introduce a versatile density-based approach to label placement that aims to put labels in uncluttered areas of an underlying 2D visualization. Our novel, image-space algorithm constructs a density map by applying kernel density estimation to the input features, i.e., the locations of the points to be labeled. In order to find a suitable position for a label where it does not overlap any features or other labels, we move it following the gradient descent of this density map. This guides labels toward nearby areas of low feature density, resulting in a layout where labels are spread around feature-dense areas. The gradient descent trajectory can be used to draw curved leaders that connect the point features to their labels. Additionally, our approach supports prioritized label placement, user-defined label-to-label and label-to-feature margins, obstacle-constrained labeling, and arbitrarily shaped labels. The proposed method is conceptually simple and can easily be implemented using OpenCV and image-processing libraries.

On the nesting of a contour dataset and its use in repair

ABSTRACTA contour dataset is a common source of data in biomedical imaging and GIS. In practice, many contour datasets violate key assumptions: contours self-intersect or intersect other contours, which can disrupt the performance of algorithms. We call such data dirty. Avoiding this issue, algorithms in the literature assume clean data. This paper considers the issue of dirty datasets, in the context of nesting.Contours are often nested inside other contours, and the nesting level of a contour is important, as it affects the position of the inside of the shape. This paper analyzes the nesting of a dirty dataset, then shows how to use this nesting analysis to repair the data. A theme is the power of image space algorithms in the presence of noise. Image space algorithms for polygon area and Boolean operations of polygons are provided.

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [18F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral/kernel model can also be used for effective post-reconstruction denoising, through the use of an EM-like image-space algorithm. Finally, we applied the proposed algorithm to reconstruction of real high-resolution dynamic [11C]SCH23390 data, showing promising results.

An image-space algorithm for immersive views in 3-manifolds and orbifolds

We describe the first image-space ray-tracing algorithm to generate interior views of flat or hyperbolic 3-manifolds, orbifolds, and similar polyhedral complexes. The complexity of our algorithm is linear in the number of echoes for a given number of polygons, compared to exponential complexity for the object-space algorithm chosen as standard.

Stereoscopic Rendering with Artistic Styles

We present a stereoscopic rendering scheme of 3D models with artistic styles including cartoon rendering contour drawing. Our scheme design separate projection matrices for both eyes and apply them to generate two images. After that, we apply artistic styles for the images. To preserve the coherence of the images, we design an image space algorithm that modifies the artistic effects of both images to reduce the difference of the artistic styles.

80-kVp CT Using Iterative Reconstruction in Image Space Algorithm for the Detection of Hypervascular Hepatocellular Carcinoma: Phantom and Initial Clinical Experience

ObjectiveTo investigate whether the low-tube-voltage (80-kVp), intermediate-tube-current (340-mAs) MDCT using the Iterative Reconstruction in Image Space (IRIS) algorithm improves lesion-to-liver contrast at reduced radiation dosage while maintaining acceptable image noise in the detection of hepatocellular carcinomas (HCC) in thin (mean body mass index, 24 ± 0.4 kg/m2) adults.Subjects and MethodsA phantom simulating the liver with HCC was scanned at 50-400 mAs for 80, 100, 120 and 140-kVp. In addition, fifty patients with HCC who underwent multiphasic liver CT using dual-energy (80-kVp and 140-kVp) arterial scans were enrolled. Virtual 120-kVP scans (protocol A) and 80-kVp scans (protocol B) of the late arterial phase were reconstructed with filtered back-projection (FBP), while corresponding 80-kVp scans were reconstructed with IRIS (protocol C). Contrast-to-noise ratio (CNR) of HCCs and abdominal organs were assessed quantitatively, whereas lesion conspicuity, image noise, and overall image quality were assessed qualitatively.ResultsIRIS effectively reduced image noise, and yielded 29% higher CNR than the FBP at equivalent tube voltage and current in the phantom study. In the quantitative patient study, protocol C helped improve CNR by 51% and 172% than protocols A and B (p < 0.001), respectively, at equivalent radiation dosage. In the qualitative study, protocol C acquired the highest score for lesion conspicuity albeit with an inferior score to protocol A for overall image quality (p < 0.001). Mean effective dose was 2.63-mSv with protocol A and 1.12-mSv with protocols B and C.ConclusionCT using the low-tube-voltage, intermediate-tube-current and IRIS help improve lesion-to-liver CNR of HCC in thin adults during the arterial phase at a lower radiation dose when compared with the standard technique using 120-kVp and FBP.

K-space reconstruction of magnetic resonance inverse imaging (K-InI) of human visuomotor systems

Using simultaneous measurements from multiple channels of a radio-frequency coil array, magnetic resonance inverse imaging (InI) can achieve ultra-fast dynamic functional imaging of the human with whole-brain coverage and a good spatial resolution. Mathematically, the InI reconstruction is a generalization of parallel MRI (pMRI), which includes image space and k-space reconstructions. Because of the auto-calibration technique, the pMRI k-space reconstruction offers more robust and adaptive reconstructions compared to the image space algorithm. Here we present the k-space InI (K-InI) reconstructions to reconstruct the highly accelerated BOLD-contrast fMRI data of the human brain to achieve 100 ms temporal resolution. Simulations show that K-InI reconstructions can offer 3D image reconstructions at each time frame with reasonable spatial resolution, which cannot be obtained using the previously proposed image space minimum-norm estimates (MNE) or linear constraint minimum variance (LCMV) spatial filtering reconstructions. The InI reconstructions of in vivo BOLD-contrast fMRI data during a visuomotor task show that K-InI offer 3 to 5 fold more sensitive detection of the brain activation than MNE and a comparable detection sensitivity to the LCMV reconstructions. The group average of the high temporal resolution K-InI reconstructions of the hemodynamic response also shows a relative onset timing difference between the visual (first) and somatomotor (second) cortices by 400 ms (600 ms time-to-peak timing difference). This robust and sensitive K-InI reconstruction can be applied to dynamic MRI acquisitions using a large-n coil array to improve the spatiotemporal resolution.

Dynamic Transparency for 3D Visualization: Design and Evaluation

Recent developments in occlusion management for 3D environments often involve the use of dynamic transparency, or "virtual X-ray vision", to promote target discovery and access in complex 3D worlds. However, there are many different approaches to achieving this effect and their actual utility for the user has yet to be evaluated. Furthermore, the introduction of semitransparent surfaces adds additional visual complexity that may actually have a negative impact on task performance. In this paper, we report on an empirical user study investigating these human aspects of dynamic transparency. Our implementation of the technique is an image-space algorithm built using modern programmable shaders to achieve real-time performance and visually pleasing results. Results from the user study indicate that dynamic transparency provides superior performance for perceptual tasks in terms of both efficiency and correctness. Subjective ratings are also firmly in favor of the method.

A New Technique for Rendering Complex Portals

In this paper, we identify a general paradigm for portal-based rendering and present an image-space algorithm for rendering complex portals. Our general paradigm is an abstraction of portal-based rendering that is independent of scene geometry. It provides a framework for flexible and dynamic scene composition by connecting cells with transformative portals. Our rendering algorithm maintains a visible volume in image-space and uses fragment culling to discard fragments outside of this volume. We discuss our implementation in OpenGL and present results that show it provides correct rendering of complex portals at interactive rates on current hardware. We believe that our work will be useful in many applications that require a means of creating dynamic and meaningful visual connections between different sets of data.

모바일을 기반으로 하는 적응적인 렌더링 영상 처리

이 논문에서는 모바일을 기반으로 하는 사진 트리 영상 랜더링을 통하여 효율적인 PDA 용 전자의 무기록(EMR ; Electronic Medical Record) 챠트를 제안하였다. 볼륨 렌더링을 위하여 최종 영상 공간 대신에 중간 영상 공간 공간 알고리즘을 사용하였고, 점 대 점 매핑으로 발생하는 Hole의 문제점을 해결하였다. 델타 트리 기반의 quad 트리를 사용함으로 볼륨 표현에 효과적이었고, 압축 효과가 높았다. 볼륨 렌더링을 사용하여 렌더링의 시간을 줄일 수 있었고, 영상기반 렌더링(image-based rendering) 을 이용한 PDA 를 사용하여 질적 향상과 효율화를 얻게 되었다. This paper presents an EMR(Electronic Medical Record) chart for efficient PDA through the quad tree image rendering based on the mobile. Using the intermediate image space algorithm instead of the final one for volume rendering, we have solved the probems of th eholes coming from the point-to-point to mapping. The quad-tree based on the delta-tree efficiently represents volume expressions and results in higher compression effects. With the volume rendering, we can decrease the rendering time and get a higher quality and efficiency for PDA through image based rendering.

Direct volume rendering of unstructured grids

This paper investigates three categories of algorithms for direct volume rendering of unstructured grids, which are image-space, object-space, and hybrid methods. We propose three new algorithms. Cell Projection algorithm, which falls into object-space category, is capable of rendering non-convex meshes through a simple yet efficient sorting schema that exploits both image and object space coherencies. Existing hybrid methods use object-then-image traversal order that enforces the processing of each cell. Thus, these algorithms perform redundant operations and do not support early ray termination. We propose a hybrid method, called Span-Buffer Ray Casting (SBRC), that can support early ray termination discarding redundant operations by employing image-then-object traversal order. Another hybrid method, called Koyamada-SBRC (K-SBRC), is proposed with the motivation of refining image-space and hybrid methods to extract the best features of them. This method is developed by blending SBRC approach with Koyamada's algorithm, which is an efficient image-space algorithm. All proposed algorithms are capable of handling acyclic non-convex meshes and generating images of acceptable quality. SBRC and K-SBRC algorithms have the additional capabilities of rendering cyclic meshes and supporting early ray termination. The proposed algorithms and Koyamada's algorithm are implemented and experimented in a common framework for analyzing their relative performance.

P-Buffer: A hidden-line algorithm in image-space

Despite the emergence of highly realistic computer-generated images, line-drawing images are still a common practice in showing the shapes and movements of three-dimensional objects. It is especially true when rendering time is critical in interactive applications such as the modeling and testing stage of computer aided design/manufacturing, computer animation, and virtual reality. Hence much effort has been devoted to provide sufficient information of the displayed objects with the least amount of time. While the techniques that determine visible surfaces in an image-space have the advantages on rendering speed and processable shapes, those that decide visible lines or line segments in an object-space are more suitable for showing hidden lines. The P-buffer algorithm introduced in this paper is a method for rendering line-drawing images with dashed hidden-lines. Being an image-space method, this algorithm preserves the low computational cost and works on a wide range of object shapes; as an extension to the Z-buffer algorithm it, moreover, discloses hidden surfaces by showing them with dashed lines. After a discussion on rendering techniques of line-drawing images, this paper presents this algorithm with pseudocode in C++ programming language and shows some experimental results as well. This image-space algorithm can be used as a compromise approach that reveals the concealed information of hidden-surface-removed views for time-critical rendering.

An algorithm for clipping lines in object and image space

A new algorithm for clipping lines against rectangular windows is described. It is suitable for computations in both object space (floating point arithmetic) and image space (integer arithmetic). The algorithm is compared with other object and image space algorithms and shown to be superior.

A New Two Dimensional Line Clipping Algorithm for Small Windows

AbstractA new algorithm for clipping lines against rectangular windows is described. It is suitable for computations in both object space (floating point arithmetic) and image space (integer arithmetic). The algorithm is compared with other object and image space algorithms and shown to be superior for small windows.

Technical note: Raster applications with GKS

Raster-based graphics applications are becoming widespread. This paper provides a critical review of the support provided within GKS (Graphical Kernal System) for such applications. The use of GKS by applications using image space algorithms and the use of GKS for the control of memory-mapped displays is discussed in depth.

An exact hidden sphere algorithm that operates in linear time

This paper presents an exact hidden line algorithm, SPHERES, that operates in linear expected time. The algorithm is exact because it works in object space, and so calculates the visible lines accurately to within the floating point tolerance of the host machine. In contrast to all image space algorithms, SPHERES' calculations take no more time for a high-resolution display. SPHERES operates on a 3-D scene composed of spheres, as in a space-filling molecular model, but nothing in the underlying concepts depends on this. In contrast to all other hidden line algorithms, SPHERES' execution time does not depend much on the depth complexity of the scene, even if it is as high as 30. This has been verified experimentally, as has the linear time dependence on the number of input spheres, up to 10,000.