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Methodology to Determine Important-Points Location for Automated Lumbar Spine Stenosis Diagnosis Procedure

Natalia, Friska and Meidia, Hira and Afriliana, Nunik and Al-Kafri, Ala S. and Sudirman, Sud (2019) Methodology to Determine Important-Points Location for Automated Lumbar Spine Stenosis Diagnosis Procedure. ICIMH 2019: Proceedings of the 2019 International Conference on Intelligent Medicine and Health. pp. 53-57.

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Official URL: https://dl.acm.org/doi/abs/10.1145/3348416.3348426

Abstract

Chronic Lower Back Pain (CLBP) is one of the major types of pain that is affecting many people around the world. Lumbar Spine Stenosis (LSS), a major cause of CLBP, requires experienced neuroradiologists to detect and diagnose. It has been reported that the number of MRI examinations around the world is increasing but the number of specialist neuroradiologists to examine and analyse them has not. This paper presents a continuation of our methodology to automatically detect the presence of LSS by analyzing lumbar spine MRI images. It details important points location-determination algorithm that can be further processed in the LSS diagnosis procedure. We use the results of our, previously developed, boundary delineation method to supply boundary points to the algorithm. The algorithm is applied to the best cut axial-view images of the intervertebral discs of 515 patients contained in the Lumbar Spine MRI dataset. The results of the important points locations are presented.

Item Type: Article
Subjects: 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming (Algorithm, Programming Language, Applications, Software, Data Security)
600 Technology (Applied Sciences) > 610 Medicine and Health > 617 Surgery, Regional Medicine, Dentistry, Ophthalmology, Otology, Audiology
Divisions: Fakultas Teknik Informatika > Program Studi Informatika
Depositing User: mr admin umn
Date Deposited: 12 Oct 2021 01:51
Last Modified: 12 Oct 2021 01:51
URI: http://kc.umn.ac.id/id/eprint/18662

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