基于GPU的实时心脏可视化系统设计与实现

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GRCVS：基于GPU的实时心脏可视化系统 GRCVS（GPU-based Real-time Cardiac Visualization System）是一种基于GPU的实时心脏可视化系统，旨在提供高效、实时的心脏可视化解决方案。该系统集成了illumination模型和context-preserving模型，以生成高质量的心脏图像同时保留重要边界信息。该系统使用CUDA编程，能够实时渲染最终图像，并提供强大的交互能力，允许用户通过简洁的界面设置各种参数以调整图像效果。知识点： 1. GRCVS系统的设计目标：提供高效、实时的心脏可视化解决方案，满足医疗研究和临床应用的需求。 2. 系统架构：GRCVS系统基于GPU，集成了illumination模型和context-preserving模型，以生成高质量的心脏图像同时保留重要边界信息。 3. 可视化技术：GRCVS系统使用CUDA编程，能够实时渲染最终图像，满足实时可视化的需求。 4. 交互能力：GRCVS系统提供强大的交互能力，允许用户通过简洁的界面设置各种参数以调整图像效果。 5. 应用场景：GRCVS系统可以应用于医疗研究和临床应用中，例如心脏疾病的诊断和治疗等。 6. 技术优势：GRCVS系统基于GPU的设计，能够提供高效、实时的心脏可视化解决方案，满足医疗研究和临床应用的需求。 7. illumination模型：illumination模型是GRCVS系统中的一个关键组件，用于生成高质量的心脏图像。 8. context-preserving模型：context-preserving模型是GRCVS系统中的另一个关键组件，用于保留重要边界信息。 9. CUDA编程：CUDA编程是GRCVS系统中的一个关键技术，用于实时渲染最终图像。 10. 医疗应用：GRCVS系统可以应用于医疗研究和临床应用中，例如心脏疾病的诊断和治疗等。 11. 图像处理技术：GRCVS系统使用图像处理技术来生成高质量的心脏图像。 12. 实时渲染：GRCVS系统使用CUDA编程，能够实时渲染最终图像，满足实时可视化的需求。 13. 用户界面：GRCVS系统提供简洁的用户界面，允许用户设置各种参数以调整图像效果。 14. 参数调整：GRCVS系统允许用户调整图像效果，例如调整图像的亮度、对比度等。 15. 图像质量：GRCVS系统可以生成高质量的心脏图像，满足医疗研究和临床应用的需求。

GRCVS: A GPU-based and real-time cardiac

visualization system

Shui Yu, Xiaoqing Liang, Kuanquan Wang, Yongfeng Yuan

School of Computer Science and Technology

Harbin Institute of Technology

Harbin, China

yushi@hit.edu.cn

, lxq.first@163.com, wangkq@hit.edu.cn, yongfeng.yuan@hit.edu.cn

Abstract—Visualization is very useful for the study of

the heart, but it is still a challenging work to display the

detailed heart because of the complex structure and

expensive computation. Very few systems have been

developed to satisfy this work specially. In this paper, we

designed and implemented a GPU-based and real-time

cardiac visualization system (GRCVS). The illumination

model and the context-preserving model are integrated

into the system, so that it can generate better images and

preserve the important boundary information at the same

time. The rendering process is programmed with CUDA,

which helps to view the final image in real time. The

system also provides strong interactive ability: it supplies

visual and concise interfaces to set various parameters

which are used to adjust image effect and user can also use

simple ways to observe the images quickly and

conveniently. The system has been proved to be valuable

for the study of the heart in biomedical field.

Keywords—visualization system; illumination model; context-

preserving model; cardiac visualization; CUDA

I. INTRODUCTION

Heart disease is one of the most serious diseases that

threaten human life. A lot of studies have been carried out to

reveal the mechanism of it. Visualization that can supply visual

and intuitive result plays a crucial role in these studies. But it is

still a challenging work to observe the detailed structure

information in real time in the existed visualization system of

heart. Due to the complex layered structures and the expensive

computing cost, very few visual platforms have been

developed to attack these difficulties.

Vassilios developed a system named Virtual Heart for

clinical skills training about interventional cardiology and

electrophysiology [1], but this system rendered the cardiac

structure with surface rendering, and cannot display the special

position between different tissues. Zhang proposed a heart

illustration platform based on GPU [2] and later introduced

another system named G-heart [3], which helps to analyze the

3D cardiac medical data and assess the electrophysiological

simulation data. Kharche proposed a high-performance

computing and visualization application of 3D virtual human

atrium [4], but the hardware requirements are relative high.

Wang et al. presented a system based on a simplified LH

histogram transfer function design method to visualize the

multi-boundary and electrophysiology simulation data

interactively [5], but it was CPU-based and not real-time.

Zhang et al. provided a visualization system to display dynamic

4D real-time multidetector computed tomographical (MDCT)

image [6] and later expanded the system to 4D cardiac MRI

and ultrasound images [7]. Khalifa et al. presented a CAD

system to analyzing cardiac first-pass MR images [8]. Nemanja

et al. implemented a system to process and visualize the ECG

signal by using smartphone [9], but Khalifa and Nemanja’s

emphases are on the functional data, not anatomic data.

Besides those systems, some other works have been done based

on VTK (Visualization Toolkit) because of its rich plugins

[10][11], but they are very complex, and not open for user, and

the optimization of existing plugins is very difficult.

In this paper, we designed and implemented an interactive

and real-time visual platform for the visualization of the heart.

The platform realizes the ray-casting algorithm based on GPU,

and builds the Blinn-Phong shading model to highlight the

interested region. It also supplies interactive ways to construct

the color and lighting transfer function. Furthermore, an

improved context-preserving model is implemented to exhibit

the internal structure information while retaining the external

contour, and generate the display effect of cutting plane.

The rest of the paper is organized as follows. Section II

describes the overall workflow of our system; section III

discusses the Blinn-phong model and the lighting transfer

function; after that, we introduce our improved context-

preserving model and the workflow in CUDA (Compute

Unified Device Architecture). The results and discussions are

presented in section IV. The conclusion of this paper and some

future work are listed in section V.

II. A

RCHITECTURE OVERVIEW

The overall workflow of our system is shown in Fig. 1.

First of all, all 2D slices of the original data to be visualized are

transferred into system. After preprocessing, they are processed

to generate 3D volume data which can be further used to

produce other 2D slices according to user custom view

direction. Secondly, the 3D volume data is rendered with ray

casting method based on GPU directly. Finally, some

interactive means for the configuration of the transfer functions

are presented during the ray casting process.

Some techniques of computer graphics and visualization

are integrated into our system. As shown in Fig. 1, the context-

preserving model and the illumination model are presented as

This work was supported by the National Nature Science Foundation of

China (Nos. 61173086)

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