Large scale medical image online three-dimensional reconstruction based on WebGL using four tier client server architecture. (April 2023)

• Record Type: Journal Article
• Authors: Li, Wei; Wang, Shanshan; Xie, Weidong; Yu, Kun; Feng, Chaolu
• Is Part Of: Information visualization. Volume 22:Number 2(2023)
• Page Start: 100
• Page End: 114
• Publication Date: 2023-04
• Subjects: Medical image -- online visualization -- 3D reconstruction -- software architecture -- WebGL; Information visualization -- Periodicals; 006.605
• DOI: 10.1177/14738716221138090
• Languages: English
• ISSNs: 1473-8716

Abstract

The development of medical device technology has led to the rapid growth of medical imaging data. The reconstruction from two-dimensional images to three-dimensional volume visualization not only shows the location and shape of lesions from multiple views but also provides intuitive simulation for surgical treatment. However, the three-dimensional reconstruction process requires the high performance execution of image data acquisition and reconstruction algorithms, which limits the application to equipments with limited resources. Therefore, it is difficult to apply on many online scenarios, and mobile devices cannot meet high-performance hardware and software requirements. This paper proposes an online medical image rendering and real-time three-dimensional (3D) visualization method based on Web Graphics Library (WebGL). This method is based on a four-tier client-server architecture and uses the method of medical image data synchronization to reconstruct at both sides of the client and the server. The reconstruction method is designed to achieve the dual requirements of reconstruction speed and quality. The real-time 3D reconstruction visualization of large-scale medical images is tested in real environments. During the interaction with the reconstruction model, users can obtain the reconstructed results in real-time and observe and analyze it from all angles. The proposed four-tier client-server architecture will provide instant visual feedback and interactive information for many medical practitioners in collaborative therapy and tele-medicine applications. The experiments also show that the method of online 3D image reconstruction is applied in clinical practice on large scale image data while maintaining high reconstruction speed and quality.