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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
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Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development
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BlueLight: An Open Source DICOM Viewer Using Low-Cost Computation Algorithm Implemented with JavaScript Using

Tseng-Tse Chen1,2, Ying-Chou Sun3,4,5, Woei-Chyn Chu2

  • 1Department of Information Management, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan.

Journal of Digital Imaging
|December 20, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a low-cost JavaScript algorithm for web-based medical imaging visualization, reducing computation time and memory usage on mobile devices. The new method enables efficient 3D rendering and DICOMweb connectivity in browsers.

Keywords:
DICOMDICOMwebJavaScriptMultiplanar reconstructionVolume renderingWebGLZero-footprint

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Area of Science:

  • Medical Imaging
  • Computer Science
  • Web Technologies

Background:

  • WebGL is common in web medical viewers but struggles with computation and memory demands on mobile devices.
  • Advanced renderings like volume rendering and multiplanar reconstruction are limited on low-cost devices.
  • Existing solutions often require high computation, hindering accessibility.

Purpose of the Study:

  • To propose a client-side, low-cost computation algorithm for 2D and 3D medical imaging visualization.
  • To reduce computation time and memory consumption for web-based medical imaging interpretation.
  • To enable advanced rendering features on resource-constrained devices.

Main Methods:

  • Developed a pure JavaScript algorithm for client-side rendering.
  • Utilized CSS transform functions combined with Digital Imaging and Communications in Medicine (DICOM) data.
  • Replaced high-computation APIs to optimize performance.
  • Implemented the algorithm in the open-source BlueLight DICOM viewer.

Main Results:

  • Significantly reduced central and graphics processing unit consumption across various web browsers.
  • Achieved sufficient rendering performance for 3D medical images with DICOM annotations.
  • Demonstrated the ability to connect to image archives via DICOMweb.

Conclusions:

  • The proposed JavaScript algorithm offers an efficient solution for web-based medical imaging visualization.
  • It overcomes limitations of computation time and memory consumption on low-cost devices.
  • The algorithm enhances accessibility of advanced medical imaging features through zero-footprint web applications.