Web-Based Medical Imaging Analysis–Leveraging Progressive Web Application for DICOM and MPR Visualization: Software Development and Validation (Preprint)

Abstract

In medical imaging, 3D visualization is vital for displaying volumetric organs, enhancing diagnosis and analysis. Multiplanar Reconstruction (MPR) improves visual and diagnostic capabilities by transforming 2D images from CT and MRI into 3D representations. Web-based DICOM viewers integrated into Picture Archiving and Communication Systems (PACS) facilitate easy access to pictures and interaction with remote data. However, the adoption of Progressive Web Applications (PWAs) for online DICOM and MPR visualization remains limited. This paper addresses this gap, leveraging PWAs for their offline access and enhanced performance.

To evaluate the integration of DICOM and MPR visualization into the web using PWAs, addressing challenges related to cross-platform compatibility, integration capabilities, and high-resolution image reconstruction for medical image visualization.

Our paper introduces a PWA which utilizes a modular design for enhancing DICOM and MPR visualization in web-based medical imaging. By integrating React.js and Cornerstone.js, the application offers seamless DICOM image processing, ensures cross-browser compatibility, and delivers a responsive user experience across multiple devices. It uses advanced interpolation techniques to make volume reconstructions more accurate. This makes MPR analysis and visualization better in a web environment, thus promising a substantial advance in medical imaging analysis.

In our approach, the performance of a DICOM and MPR-based PWA for medical image visualization and reconstruction was evaluated through comprehensive experiments. The application excelled in loading time and volume reconstruction, particularly in Chrome, while Firefox showed superior performance in viewing slices. Utilizing a dataset of 22 CT peripheral artery patients, the experiments underscored the application's robust performance, with Chrome outperforming other browsers in both LAN and WAN settings. In addition, the application's accuracy in MPR reconstructions was validated with an error margin of less than 0.05 mm and outperformed the state-of-the-art by 84% to 98% in loading and volume rendering time.

The paper highlights advancements in DICOM and MPR visualization using PWAs, addressing the gaps in web-based medical imaging. By exploiting PWA features like offline access and improved performance, we have significantly advanced medical imaging technology, focusing on cross-platform compatibility, integration efficiency, and speed. Our application outperforms existing platforms for handling complex MPR analyses and accurate analysis for medical imaging, validated by a peripheral artery CT imaging.