TY  - CONF
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857090705&doi=10.1109%2fNatPC.2011.6136338&partnerID=40&md5=0a1a5f528d3b6ff8eca50be9f2e3011c
A1  - Kumar, D.
A1  - Hani, A.F.M.
A1  - Malik, A.S.
A1  - Kamil, R.
A1  - Razak, R.
A1  - Kiflie, A.
Y1  - 2011///
SN  - 9781457718847
N1  - cited By 3; Conference of 3rd National Postgraduate Conference - Energy and Sustainability: Exploring the Innovative Minds, NPC 2011 ; Conference Date: 19 September 2011 Through 20 September 2011; Conference Code:88531
N2  - In this paper the morphological, molecular (biochemical) and mechanical features of osteoarthritis and various modalities that can be used to detect knee osteoarthritis (OA) at an early stage are discussed. Based on the facts and other supporting evidences, it is hypothesised that early knee OA detection can be improved by combining the assessment of cartilage thickness and water content of articular cartilage. The main objective of this research work is to develop a non-invasive analysis and diagnostic tool with high sensitivity and specificity using quantitative magnetic resonance (qMR) imaging that can be used to detect knee osteoarthritis below stage 1 with reference to the International Cartilage Repair Society (ICRS) grading system. Research has shown that there is a relationship between water content of cartilage with quantitative value of magnetic resonance (qMR) signals due to the presence of hydrogen in human knee cartilage. It is clear that the current methods (imaging modality, feature selection and classification) of detecting any single molecular changes in the articular cartilage on their own are not able to provide sufficient distinguishing capability of early OA. This research project points toward a multi-feature detection and classification for a successful diagnostic tool. © 2011 IEEE.
KW  - Articular cartilages; Cartilage repair; Cartilage thickness; Diagnostic tools; Early detection; Feature selection and classification; Grading system; High sensitivity; Human knee; Imaging modality; Knee osteoarthritis; Mechanical feature; Molecular changes; Non-invasive; Non-invasive diagnostics; PG content; qMR; Quantitative magnetic resonances; Quantitative values; thickness
KW  -  Diagnostic products; Hydrogen; Magnetic resonance; Research; Sodium; Sustainable development; Water
KW  -  Cartilage
ID  - scholars1607
TI  - Development of a non-invasive diagnostic tool for early detection of knee osteoarhritis
CY  - Perak
AV  - none
ER  -