TY - GEN
T1 - Accuracy and precision analysis of 3-d cancer atlas registration for targeted prostate biopsy via predictive deformation modeling
AU - Narayanan, Ramkrishnan
AU - Barqawi, Albaha
AU - Crawford, David
AU - Shinohara, Katsuto
AU - Simoneau, Anne
AU - Shen, Dinggang
AU - Davatzikos, Christos
AU - Suri, Jasjit
PY - 2008/12/1
Y1 - 2008/12/1
N2 - New biopsy plans are being proposed to improve the detection of significant cancers in the prostate. Among these methods are those that suggest new needle sites, more sites, and also optimal orientations for targeted biopsy. The key challenge being the maximization of the detection of cancers while at the same time using small number of needles to reduce risk of patient anxiety, bleeding and incontinence. To address the fairly consistent spatial inhomogeneity of cancers found among individuals within the population, researchers constructed a cancer atlas of the prostate. The atlas displayed voxel-wise likelihood of cancer occurrences within the prostate, and an optimal 6-7 biopsy scheme to maximize cancer detection. To be useful clinically, the atlas must be warped to the patient's transrectal ultrasound image (TRUS). Previously we suggested use of a shape model to register the surface of the atlas to the segmented prostate surface from the TRUS image reducing the degrees of freedom and computation time. This surface correspondence was used to elastically warp the entire atlas volume to register with the subject. Here we discuss a fast predictive approach where elastic volume warps are also used to train the shape model offline resulting in the construction of an extended shape basis. The surface registration of the atlas and the segmented subject surface yields projections on the extended shape basis from which volume warps can be directly inferred. The accuracy and precision of this predictive method was compared with the original method to analyze the speed-accuracy and precision trade off. We found the average accuracy and precision to be less than 1 mm.
AB - New biopsy plans are being proposed to improve the detection of significant cancers in the prostate. Among these methods are those that suggest new needle sites, more sites, and also optimal orientations for targeted biopsy. The key challenge being the maximization of the detection of cancers while at the same time using small number of needles to reduce risk of patient anxiety, bleeding and incontinence. To address the fairly consistent spatial inhomogeneity of cancers found among individuals within the population, researchers constructed a cancer atlas of the prostate. The atlas displayed voxel-wise likelihood of cancer occurrences within the prostate, and an optimal 6-7 biopsy scheme to maximize cancer detection. To be useful clinically, the atlas must be warped to the patient's transrectal ultrasound image (TRUS). Previously we suggested use of a shape model to register the surface of the atlas to the segmented prostate surface from the TRUS image reducing the degrees of freedom and computation time. This surface correspondence was used to elastically warp the entire atlas volume to register with the subject. Here we discuss a fast predictive approach where elastic volume warps are also used to train the shape model offline resulting in the construction of an extended shape basis. The surface registration of the atlas and the segmented subject surface yields projections on the extended shape basis from which volume warps can be directly inferred. The accuracy and precision of this predictive method was compared with the original method to analyze the speed-accuracy and precision trade off. We found the average accuracy and precision to be less than 1 mm.
KW - Atlas
KW - Biopsy
KW - Cancer
KW - Prostate
KW - Registration
KW - Ultrasound
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M3 - Conference contribution
AN - SCOPUS:62949142491
SN - 9780889867215
T3 - Proceedings of the 6th IASTED International Conference on Biomedical Engineering, BioMED 2008
SP - 222
EP - 226
BT - Proceedings of the 6th IASTED International Conference on Biomedical Engineering, BioMED 2008
T2 - 6th IASTED International Conference on Biomedical Engineering, BioMED 2008
Y2 - 13 February 2008 through 15 February 2008
ER -