TY - GEN
T1 - Adaptive H-extrema for automatic immunogold particle detection
AU - Thibault, Guillaume
AU - Iljin, Kristiina
AU - Arthur, Christopher
AU - Shafran, Izhak
AU - Gray, Joe
PY - 2013
Y1 - 2013
N2 - Quantifying concentrations of target molecules near cellular structures, within cells or tissues, requires identifying the gold particles in immunogold labelled images. In this paper, we address the problem of automatically detect them accurately and reliably across multiple scales and in noisy conditions. For this purpose, we introduce a new contrast filter, based on an adaptive version of the H-extrema algorithm. The filtered images are simplified with a geodesic reconstruction to precisely segment the candidates. Once the images are segmented, we extract classical features and then classify using the majority vote of multiple classifiers. We characterize our algorithm on a pilot data and present results that demonstrate its effectiveness.
AB - Quantifying concentrations of target molecules near cellular structures, within cells or tissues, requires identifying the gold particles in immunogold labelled images. In this paper, we address the problem of automatically detect them accurately and reliably across multiple scales and in noisy conditions. For this purpose, we introduce a new contrast filter, based on an adaptive version of the H-extrema algorithm. The filtered images are simplified with a geodesic reconstruction to precisely segment the candidates. Once the images are segmented, we extract classical features and then classify using the majority vote of multiple classifiers. We characterize our algorithm on a pilot data and present results that demonstrate its effectiveness.
KW - Adaptive H-extrema
KW - Immunogold particle detection
KW - Mathematical morphology
KW - Pattern recognition
UR - http://www.scopus.com/inward/record.url?scp=84893174176&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893174176&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-41827-3_30
DO - 10.1007/978-3-642-41827-3_30
M3 - Conference contribution
AN - SCOPUS:84893174176
SN - 9783642418266
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 238
EP - 245
BT - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 18th Iberoamerican Congress, CIARP 2013, Proceedings
T2 - 18th Iberoamerican Congress on Pattern Recognition, CIARP 2013
Y2 - 20 November 2013 through 23 November 2013
ER -