TY - GEN
T1 - Curvilinear structures extraction in cluttered bioimaging data with discrete optimization methods
AU - Honnorat, Nicolas
AU - Vaillant, Régis
AU - Duncan, James S.
AU - Paragios, Nikos
PY - 2011
Y1 - 2011
N2 - Filamentary structures extraction in medical and biological images is a challenging problem. Muscular/Neural fibers, neurites and blood arteries are some examples. Their delineation is particularly problematic due to the lack of solid visual support that is also compromised by the presence of clutter and low signal to noise ratios. In this article, we propose a modular approach to curvilinear structures extraction based on recent advances in discrete optimization on the basis of aggregate clustering. Given an initial clustering of the detected points, first a pair-wise Markov Random Field (MRF) is considered to determine consistent elongated structures while penalizing their number and rejecting outliers. The outcome of this process is then locally refined through a non-submodular MRF aiming at center-line extraction process and guided by local geometric consistency between segments expressing the intra-cluster variability. Promising results for microtubules delineation in TIRFM images as well as for guidewires segmentation in fluoroscopic images demonstrate the potentials of the method.
AB - Filamentary structures extraction in medical and biological images is a challenging problem. Muscular/Neural fibers, neurites and blood arteries are some examples. Their delineation is particularly problematic due to the lack of solid visual support that is also compromised by the presence of clutter and low signal to noise ratios. In this article, we propose a modular approach to curvilinear structures extraction based on recent advances in discrete optimization on the basis of aggregate clustering. Given an initial clustering of the detected points, first a pair-wise Markov Random Field (MRF) is considered to determine consistent elongated structures while penalizing their number and rejecting outliers. The outcome of this process is then locally refined through a non-submodular MRF aiming at center-line extraction process and guided by local geometric consistency between segments expressing the intra-cluster variability. Promising results for microtubules delineation in TIRFM images as well as for guidewires segmentation in fluoroscopic images demonstrate the potentials of the method.
KW - Curvilinear structures
KW - Discrete optimization
KW - Guide Wire Segmentation
KW - Markov Random Fields
KW - Microtubules
UR - http://www.scopus.com/inward/record.url?scp=80055060658&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80055060658&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2011.5872651
DO - 10.1109/ISBI.2011.5872651
M3 - Conference contribution
AN - SCOPUS:80055060658
SN - 9781424441280
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 1353
EP - 1357
BT - 2011 8th IEEE International Symposium on Biomedical Imaging
T2 - 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11
Y2 - 30 March 2011 through 2 April 2011
ER -