Thisresearch is a collaborative project between Universitas Multimedia Nusantara (Indonesia)
and Liverpool John Moores University (United Kingdom) in the area of medical image
analysis and processing. Usually, Magnetic Resonance Imaging (MRI) scans of the patient’s
lumbar spine is used to check if any of the four possible causes of lower back pain discussed
earlier occurred. However, this process may be time-consuming due to a large amount of data
that the physicians must observe and take into account. This project aims at developing a
methodology for automatic detection of disc herniation in Magnetic Resonance Images (MRI)
of lumbar spine using Artificial Intelligence techniques. Urgencies of this study is:
Herniation of spinal disc is one of the main causes of Chronic Lower Back Pain (CLBP) and
currently there is no existing solution to assist physicians in their task of identifying the cause
of CLBP. They have to manually go through a series of MRIs and view them from different
views. The process is a laborious task and can take up much of their time. This project will
utilise existing Artificial Intelligence and Machine Learning techniques to scan the images
and in the first year present the physicians with the location of areas of interest which they
can review hence improve the efficiency and effectiveness of the overall diagnosis process by
the area of the spinal disc has been labelled, its shape features can be calculated. In the second
year perhaps the proposed methodology will be using the properties of the MRIs to detect
spinal disc areas and detect any presence of herniation from the shape of the discs.
Research outputs include research reports each year, scientific publications (International
Journal Scopus Indexed each year and International Conference each year), and the presence
of methods and algorithms in the second year. The results of this study are closely related to
the achievement of the UMN research plan because it is the focus of the UMN research field:
ICT Based and the research output can increase UMN’s publications.