TY - GEN
T1 - Declustering n-connected components for segmentation of iodine implants in C-arm fluoroscopy images
AU - Di San Filippo, Chiara Amat
AU - Fichtinger, Gabor
AU - Morris, William James
AU - Salcudean, Septimiu E.
AU - Dehghan, Ehsan
AU - Fallavollita, Pascal
PY - 2013
Y1 - 2013
N2 - Dynamic dosimetry is becoming the standard to evaluate the quality of radioactive implants during brachytherapy. It is essential to obtain a 3D visualization of the implanted seeds and their relative position to the prostate. For this, a robust and precise segmentation of the seeds in 2D X-ray is required. First, implanted seeds are segmented using a region-based implicit active contour approach. Then, n-seed clusters are resolved using an efficient template based approach. A collection of 55 C-arm images from 10 patients are used to validate the proposed algorithm. Compared to manual ground-truth segmentation of 6002 seeds, 98.7% of seeds were automatically detected and declustered showing a false-positive rate of only 1.7%. Results indicate the proposed method is able to perform the identification and annotation processes of seeds on par with a human expert, constituting a viable alternative to the traditional manual segmentation approach.
AB - Dynamic dosimetry is becoming the standard to evaluate the quality of radioactive implants during brachytherapy. It is essential to obtain a 3D visualization of the implanted seeds and their relative position to the prostate. For this, a robust and precise segmentation of the seeds in 2D X-ray is required. First, implanted seeds are segmented using a region-based implicit active contour approach. Then, n-seed clusters are resolved using an efficient template based approach. A collection of 55 C-arm images from 10 patients are used to validate the proposed algorithm. Compared to manual ground-truth segmentation of 6002 seeds, 98.7% of seeds were automatically detected and declustered showing a false-positive rate of only 1.7%. Results indicate the proposed method is able to perform the identification and annotation processes of seeds on par with a human expert, constituting a viable alternative to the traditional manual segmentation approach.
UR - http://www.scopus.com/inward/record.url?scp=84879643734&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84879643734&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-38568-1_11
DO - 10.1007/978-3-642-38568-1_11
M3 - Conference contribution
AN - SCOPUS:84879643734
SN - 9783642385674
VL - 7915 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 101
EP - 110
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 4th International Conference on Information Processing in Computer-Assisted Interventions, IPCAI 2013
Y2 - 26 June 2013 through 26 June 2013
ER -