A Web-based Dicom Image and Plane Viewer

Priya Darshini B, D. N., Gokul B, S. B
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Abstract

Preclinical research, clinical diagnosis, and treatment can all benefit from the information that a medical image can offer. Due to the increased usage of digital medical imaging, numerous researchers are actively creating medical image processing algorithms and systems to provide the clinical community with improved results, such as accurate clinical parameters or processed images from the original images. We describe a Web-based DICOM reader in this work that was created solely using web technology, specifically Python, Streamlit, and Docker. When it comes to programming languages, Python has established itself as a competitor to MATLAB and Julia, two prominent scientific programming languages. In this work, we examine the potential of Python and Docker as co-implementers of the DICOM viewer. A demonstration field is available to new users, for learning purposes. Three different types of image planes namely axial, coronal, and sagittal are also available, which helps doctors readily detect cancers. Additionally, we can adjust the image plane's threshold levels to suit our needs. We also provide a JSON version of the website for use in forthcoming research initiatives.
基于web的Dicom图像和平面查看器
临床前研究、临床诊断和治疗都可以从医学图像提供的信息中受益。由于数字医学成像的使用越来越多,许多研究人员正在积极地创建医学图像处理算法和系统,为临床社区提供改进的结果,例如准确的临床参数或从原始图像处理后的图像。在本文中,我们描述了一个基于web的DICOM阅读器,它完全使用web技术(特别是Python、Streamlit和Docker)创建。说到编程语言,Python已经成为MATLAB和Julia这两种著名的科学编程语言的竞争对手。在这项工作中,我们研究了Python和Docker作为DICOM查看器的共同实现者的潜力。一个演示字段可供新用户使用,用于学习目的。三种不同的图像平面,即轴状、冠状和矢状,也可以帮助医生轻松地检测癌症。此外,我们可以调整图像平面的阈值水平,以满足我们的需要。我们还提供了一个JSON版本的网站,以供未来的研究计划使用。
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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