Optimizing the visual effects of 3D rendering in medical imaging: a technical review

doi:10.11996/JG.j.2095-302X.2024050879

Abstract

Abstract:

Medical imaging is a critical field in medicine, utilizing techniques such as magnetic resonance imaging (MRI), computed tomography (CT) scans, ultrasound (US), X-rays, and positron emission tomography (PET) scans. These medical images are generated through various imaging techniques. In this context, 3D rendering has emerged as a pivotal visualization tool that plays a significant role in visualizing anatomical structures, enabling accurate diagnosis, effective treatment planning, and precise surgical interventions. This analysis examined the current state of research on optimizing visualization effects in 3D rendering technology within medical imaging. First, two fundamental 3D rendering techniques were introduced, providing a foundation for understanding the technological landscape. Following this, the discussion examined recent advancements in visualization optimization, focusing on two main areas: technical optimization and framework optimization. Technical optimization involved refining algorithms and methods to improve image quality and rendering speed. Framework optimization, on the other hand, focused on the integration of rendering technologies into broader software systems to enhance performance and usability. A comparative analysis of various optimization techniques was presented, highlighting their characteristics, application scenarios, and respective strengths and weaknesses. This comparison served as a reference for researchers and practitioners in selecting appropriate techniques for their specific needs. Evaluating the effectiveness of 3D rendering was another crucial aspect covered in this analysis. Both subjective and objective evaluation methods were explored to provide a comprehensive assessment of visualization quality. The analysis also discussed potential challenges posed by technological advancements, such as increased algorithm complexity, decreased rendering efficiency, and suboptimal real-time performance, as well as exploring potential solutions. Future directions for optimizing 3D rendering and visualization effects were explored.

Key words: medical imaging, three-dimensional rendering, transfer function, ray casting, global illumination, deep learning

CLC Number:

XU Dandan, CUI Yong, ZHANG Shiqian, LIU Yucong, LIN Yusong. Optimizing the visual effects of 3D rendering in medical imaging: a technical review[J]. Journal of Graphics, 2024, 45(5): 879-891.

Figures/Tables 14

Fig. 1 The CT images sequence used in 3D medical rendering[4]

Fig. 2 Visualization of X-ray equipment and medical image datasets ((a) The X-ray C-arm system in a clinical intervention; (b) The degrees of rotational freedom of the C-arm geometry; (c) A 3D data set, acquired using the X-ray C-arm system[5])

Fig. 3 Structural overview diagram

Table 1 Comparison table of two basic 3D rendering techniques

渲染技术	特点	使用场景	优点	缺点
等值面渲染	基于等值面提取，显示特定数值的体素	显示解剖结构或病变表面	有助于表面形状分析	难以处理复杂的内部结构
直接体绘制	直接对体数据进行渲染，无需将数据转换为其他几何形状	可视化体数据内部结构	呈现内部细节，对密集数据集表现较好	可能产生视觉混淆，不适用于强调表面特征

Fig. 4 Marching cube[12]

Fig. 5 Level of detail rendering for interactive exploration ((a) Rendering of isosurfaces in the original datasets at full image resolution; (b) Rendering the isosurfaces in the original datasets at 1/4 the image resolution and upscaling to full image resolution; (c) Rendering the isosurfaces in the low-pass filtered and down-sampled datasets with half the resolution in each dimension at full image resolution[14])

Fig. 6 Overview of direct volume rendering pipeline

Fig. 7 Sampling steps of direct volume rendering

Table 2 Comparison table of 3D rendering visualization effect optimization technology

渲染技术	特点	使用场景	优点	缺点
传递函数	体数据映射到图像属性	强调特定范围或结构	提供用户控制，优化可视化效果	调整参数需要一定专业知识
光线投射	跟踪光线路径计算颜色和亮度	处理非平面表面和实体	速度快	未考虑复杂光照
全局照明	模拟光的多次反射和折射	需要高度真实感的场景	光影效果逼真	计算复杂度高，实时性差
环境光遮蔽	不直接计算光线路径或分布，基于局部情况模拟阴影效果	实时性要求高、细节要求不那么精确的场景	计算效率高，适用性广	可能产生不真实的阴影，对细节的呈现不够精确
深度学习	灵活，选择度高	用于多种渲染任务	高质量渲染	计算成本高，训练复杂

Fig. 8 Non-enhanced 3-D CT images of multiple traumatic fractures of the spine and pelvis ((a)-(b) Both CR and VR demonstrate multiple fractures of the ribs, lumbal transverse processes, sacrum, and pubic bones[61])

Fig. 9 Achieved results combining directional ambient occlusion and shadow generation ((a) Bonsai; (b) Backpack; (c) CT-Knee; (d) Foot. On the left, emission and absorption illumination model with directional occlusion; On the right, shadows with Blinn-Phong shading are added[63])

Fig. 10 Reconstruct transfer functions with automatic differentiation ((a) Image rendered with the initialized transfer function; (b) Image rendered with the reconstructed transfer function; (c) Reference image)

Fig. 11 System architecture and workflow[89]

Table 3 Comparison of methods for optimizing 3D rendering visual effects

方法	任务	数据集	SSIM	PSNR/dB
路径追踪^[50]	全局照明	Backpack	0.997	49.663
路径追踪^[50]	全局照明	Wrasse	0.998	53.545
DVAO^[65]	环境光遮挡	Chameleon	0.866	-
GAN+cGAN^[67]	模拟全局照明	Deep illumination	0.968	34.170
DNN^[81]	图像合成	CT-chest	-	24.900
可微分渲染^[86]	TF优化	CT-chest	0.990	36.700
可微分渲染^[86]	TF优化	Tooth	0.988	34.800

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