PIAA: Pre-imaging all-round assistant for digital radiography.

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Accounts of Chemical Research Pub Date : 2024-08-08 DOI:10.3233/THC-240639

Jie Zhao, Jianqiang Liu, Shijie Wang, Pinzheng Zhang, Wenxue Yu, Chunfeng Yang, Yudong Zhang, Yang Chen

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Abstract

Background: In radiography procedures, radiographers' suboptimal positioning and exposure parameter settings may necessitate image retakes, subjecting patients to unnecessary ionizing radiation exposure. Reducing retakes is crucial to minimize patient X-ray exposure and conserve medical resources.

Objective: We propose a Digital Radiography (DR) Pre-imaging All-round Assistant (PIAA) that leverages Artificial Intelligence (AI) technology to enhance traditional DR.

Methods: PIAA consists of an RGB-Depth (RGB-D) multi-camera array, an embedded computing platform, and multiple software components. It features an Adaptive RGB-D Image Acquisition (ARDIA) module that automatically selects the appropriate RGB camera based on the distance between the cameras and patients. It includes a 2.5D Selective Skeletal Keypoints Estimation (2.5D-SSKE) module that fuses depth information with 2D keypoints to estimate the pose of target body parts. Thirdly, it also uses a Domain expertise (DE) embedded Full-body Exposure Parameter Estimation (DFEPE) module that combines 2.5D-SSKE and DE to accurately estimate parameters for full-body DR views.

Results: Optimizes DR workflow, significantly enhancing operational efficiency. The average time required for positioning patients and preparing exposure parameters was reduced from 73 seconds to 8 seconds.

Conclusions: PIAA shows significant promise for extension to full-body examinations.

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PIAA：数字放射成像的成像前全能助手。

背景：在放射摄影过程中，放射技师的定位和曝光参数设置不理想可能导致图像重拍，使患者受到不必要的电离辐射照射。减少重拍对于减少患者的 X 射线照射和节约医疗资源至关重要：我们提出了一种数字放射成像（DR）成像前全方位助手（PIAA），利用人工智能（AI）技术来增强传统的 DR：PIAA 由一个 RGB-D 深度（RGB-D）多摄像头阵列、一个嵌入式计算平台和多个软件组件组成。它具有自适应 RGB-D 图像采集 (ARDIA) 模块，可根据摄像头与患者之间的距离自动选择合适的 RGB 摄像头。它包括一个 2.5D 选择性骨骼关键点估计（2.5D-SSKE）模块，该模块将深度信息与 2D 关键点融合在一起，以估计目标身体部位的姿势。第三，它还使用了领域专业技术（DE）嵌入式全身曝光参数估计（DFEPE）模块，该模块结合了 2.5D-SSKE 和 DE，可精确估计全身 DR 视图的参数：优化 DR 工作流程，显著提高操作效率。定位患者和准备曝光参数所需的平均时间从 73 秒减少到 8 秒：结论：PIAA 很有希望扩展到全身检查。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.

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