Modern Image-Guided Surgery: A Narrative Review of Medical Image Processing and Visualization

可视化 计算机科学 背景(考古学) 数据科学 主流 虚拟现实 增强现实 图像处理 多样性(控制论) 模式 医学影像学 透视图(图形) 创造性可视化 多媒体 人机交互 人工智能 图像(数学) 社会科学 神学 生物 社会学 古生物学 哲学
作者
Zhefan Lin,Lei Chen,L. Yang
出处
期刊:Sensors [MDPI AG]
卷期号:23 (24): 9872-9872 被引量:26
标识
DOI:10.3390/s23249872
摘要

Medical image analysis forms the basis of image-guided surgery (IGS) and many of its fundamental tasks. Driven by the growing number of medical imaging modalities, the research community of medical imaging has developed methods and achieved functionality breakthroughs. However, with the overwhelming pool of information in the literature, it has become increasingly challenging for researchers to extract context-relevant information for specific applications, especially when many widely used methods exist in a variety of versions optimized for their respective application domains. By being further equipped with sophisticated three-dimensional (3D) medical image visualization and digital reality technology, medical experts could enhance their performance capabilities in IGS by multiple folds. The goal of this narrative review is to organize the key components of IGS in the aspects of medical image processing and visualization with a new perspective and insights. The literature search was conducted using mainstream academic search engines with a combination of keywords relevant to the field up until mid-2022. This survey systemically summarizes the basic, mainstream, and state-of-the-art medical image processing methods as well as how visualization technology like augmented/mixed/virtual reality (AR/MR/VR) are enhancing performance in IGS. Further, we hope that this survey will shed some light on the future of IGS in the face of challenges and opportunities for the research directions of medical image processing and visualization.

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