A Web-based Dicom Image and Plane Viewer

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.