TY - GEN
T1 - One-class acoustic characterization applied to blood detection in IVUS
AU - O'Malley, Sean M.
AU - Naghavi, Morteza
AU - Kakadiaris, Ioannis A.
PY - 2007
Y1 - 2007
N2 - Intravascular ultrasound (IVUS) is an invasive imaging modality capable of providing cross-sectional images of the interior of a blood vessel in real time and at normal video framerates (10-30 frames/s). Low contrast between the features of interest in the IVUS imagery remains a confounding factor in IVUS analysis; it would be beneficial therefore to have a method capable of detecting certain physical features imaged under IVUS in an automated manner. We present such a method and apply it to the detection of blood. While blood detection algorithms are not new in this field, we deviate from traditional approaches to IVUS signal characterization in our use of 1-class learning. This eliminates certain problems surrounding the need to provide "foreground" and "background" (or, more generally, n-class) samples to a learner. Applied to the blood-detection problem on 40 MHz recordings made in vivo in swine, we are able to achieve ∼95% sensitivity with ∼90% specificity at a radial resolution of ∼600 μm.
AB - Intravascular ultrasound (IVUS) is an invasive imaging modality capable of providing cross-sectional images of the interior of a blood vessel in real time and at normal video framerates (10-30 frames/s). Low contrast between the features of interest in the IVUS imagery remains a confounding factor in IVUS analysis; it would be beneficial therefore to have a method capable of detecting certain physical features imaged under IVUS in an automated manner. We present such a method and apply it to the detection of blood. While blood detection algorithms are not new in this field, we deviate from traditional approaches to IVUS signal characterization in our use of 1-class learning. This eliminates certain problems surrounding the need to provide "foreground" and "background" (or, more generally, n-class) samples to a learner. Applied to the blood-detection problem on 40 MHz recordings made in vivo in swine, we are able to achieve ∼95% sensitivity with ∼90% specificity at a radial resolution of ∼600 μm.
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U2 - 10.1007/978-3-540-75757-3_25
DO - 10.1007/978-3-540-75757-3_25
M3 - Conference contribution
C2 - 18051060
AN - SCOPUS:84883843367
SN - 9783540757566
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 202
EP - 209
BT - Medical Image Computing and Computer-Assisted Intervention - 10th International Conference, Proceedings
PB - Springer-Verlag
T2 - 10th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2007
Y2 - 29 October 2007 through 2 November 2007
ER -