eprintid: 9738
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/97/38
datestamp: 2023-11-09 16:36:23
lastmod: 2023-11-09 16:36:23
status_changed: 2023-11-09 16:29:42
type: conference_item
metadata_visibility: show
creators_name: Hardjasudjana, A.W.
creators_name: Kosalishkwaran, G.
creators_name: Parasuraman, S.
creators_name: Elamvazhuthi, I.
creators_name: Jeba Singh, D.K.
creators_name: Deisy, C.
creators_name: Padmavathy, S.
title: Image Analysis of Spine and Related Mechanical Investigations
ispublished: pub
keywords: Artificial intelligence; Computer aided engineering; Fatigue of materials; Finite element method; Image analysis; Image segmentation, Axial rotation; CT-scan images; Degenerative disc disease; Low back pain; Lumbar regions; Lumbar spines; Range of motions; Shearing force, Computerized tomography
note: cited By 0; Conference of 8th IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017 ; Conference Date: 14 December 2017 Through 16 December 2017; Conference Code:142125
abstract: Low back pain is a spinal-related problem mainly caused by degenerative disc disease. Throughout the spine, the lumbar region is the most prone to the disease since it supports the upper torso by transmitting compressive and shearing forces to the lower body during everyday activities. The study is focused on modeling a lumbar segment of a healthy L5-S1 by utilising image processing and computer-aided engineering to translate CT scan image into meshed finite element model. This study also involved the measurement the range of motion of the lumbar region by means of an in-vivo method. The result shows that the flexion, extension and axial rotation range of motion varies by 15-18 degrees compared to the literature, which may have been caused by in-vivo factors such as fatigue, sway and other measurement variability. The in-vivo results are then applied to the proposed finite Element Model as inputs and related investigations on spine vertebrae and disc are presented. Comparatively, the in-vivo results provides similar correlation, but variations observes quantitatively because of factors such as fatigue and sway of subjects. Further analysis will be done on stresses and moments. © 2017 IEEE.
date: 2018
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057978732&doi=10.1109%2fICCIC.2017.8524572&partnerID=40&md5=f7a91ed6b811a9225975ac96ba6e79e7
id_number: 10.1109/ICCIC.2017.8524572
full_text_status: none
publication: 2017 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017
refereed: TRUE
isbn: 9781509066209
citation:   Hardjasudjana, A.W. and Kosalishkwaran, G. and Parasuraman, S. and Elamvazhuthi, I. and Jeba Singh, D.K. and Deisy, C. and Padmavathy, S.  (2018) Image Analysis of Spine and Related Mechanical Investigations.  In: UNSPECIFIED.