Large Scale Medical Image Analysis

This project is aimed at exploring practical ways to analyze medical images on a large scale. It involves developing effective methods to process and analyze these images with precision and accuracy. By utilising  the power of advanced computing techniques, we aim to extract meaningful insights that can empower healthcare professionals to make informed decisions.

The aims of the project is as follows:

  • To determine the relative level of DICOM standard compliance of medical images
  • To determine the feasibility of automatically classifying medical images using
    DICOM metadata
Project Members
Lighton Phiri
Academic Staff
University of Zambia
Elijah Chileshe
Postgraduate Student
University of Zambia
Publications
2024
Phiri, Lighton, Ernest Obbie Zulu, Elijah Chileshe, Andrew Shawa, Wilkins Sikazwe, John Mwanza, and Brighton Mwaba. 2024. “User Centred Design And Implementation Of Useful Picture Archiving And Communication Systems For Effective Radiological Workflows In Public Health Facilities In Zambia”. In South African Institute Of Computer Scientists And Information Technologists. South Africa.
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Chileshe, Elijah, Lighton Phiri, and Claytone Sikasote. (2023) 2024. “Evaluating Dicom Compliance For Medical Images In Public Health Facilities In Zambia”. Lusaka: The University of Zambia.
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2023
Chileshe, Elijah, and Lighton Phiri. (2023) 2023. “Large-Scale Analysis Of Medical Image Metadata”. In 2023 Pan African Conference On Science, Computing And Telecommunications (Pact 2023). Lusaka, Zambia: Zambia ICT Journal. https://ictjournal.icict.org.zm/index.php/icict/article/view/277.
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