Optimizing the visual effects of 3D rendering in medical imaging:a technical review
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.
medical imagingthree-dimensional renderingtransfer functionray castingglobal illuminationdeep learning
NETL
NSTL
万方数据
