Automatic analysis of trabecular bone structure from knee MRI
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Standard
Automatic analysis of trabecular bone structure from knee MRI. / Marques, Joselene; Granlund, Rabia; Lillholm, Martin; Pettersen, Paola C.; Dam, Erik B. .
I: Computers in Biology and Medicine, Bind 42, Nr. 7, 2012, s. 735-742.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - JOUR
T1 - Automatic analysis of trabecular bone structure from knee MRI
AU - Marques, Joselene
AU - Granlund, Rabia
AU - Lillholm, Martin
AU - Pettersen, Paola C.
AU - Dam, Erik B.
N1 - Copyright © 2012 Elsevier Ltd. All rights reserved.
PY - 2012
Y1 - 2012
N2 - We investigated the feasibility of quantifying osteoarthritis (OA) by analysis of the trabecular bone structure in low-field knee MRI. Generic texture features were extracted from the images and subsequently selected by sequential floating forward selection (SFFS), following a fully automatic, uncommitted machine-learning based framework. Six different classifiers were evaluated in cross-validation schemes and the results showed that the presence of OA can be quantified by a bone structure marker. The performance of the developed marker reached a generalization area-under-the-ROC (AUC) of 0.82, which is higher than the established cartilage markers known to relate to the OA diagnosis.
AB - We investigated the feasibility of quantifying osteoarthritis (OA) by analysis of the trabecular bone structure in low-field knee MRI. Generic texture features were extracted from the images and subsequently selected by sequential floating forward selection (SFFS), following a fully automatic, uncommitted machine-learning based framework. Six different classifiers were evaluated in cross-validation schemes and the results showed that the presence of OA can be quantified by a bone structure marker. The performance of the developed marker reached a generalization area-under-the-ROC (AUC) of 0.82, which is higher than the established cartilage markers known to relate to the OA diagnosis.
U2 - 10.1016/j.compbiomed.2012.04.005
DO - 10.1016/j.compbiomed.2012.04.005
M3 - Journal article
C2 - 22579046
VL - 42
SP - 735
EP - 742
JO - Computers in Biology and Medicine
JF - Computers in Biology and Medicine
SN - 0010-4825
IS - 7
ER -
ID: 40995413