Using ASM in CT data segmentaion for prostate radiotherapy

Authors:
Andrzej Skalski;Artur Kos;Tomasz Zieliński
Affiliations:
Department of Measurement and Electronics, AGH University of Science and Technology, Kraków, Poland;Department of Telecommunications, AGH University of Science and Technology, Kraków, Poland;Department of Telecommunications, AGH University of Science and Technology, Kraków, Poland
Venue:
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
Year:
2012

Citing 7
Cited 0

Trainable method of parametric shape description

Image and Vision Computing - Special issue: BMVC 1991
Active shape models—their training and application

Computer Vision and Image Understanding
Automatic 3D ASM Construction via Atlas-Based Landmarking and Volumetric Elastic Registration

IPMI '01 Proceedings of the 17th International Conference on Information Processing in Medical Imaging
A review of active appearance models

IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Automatic MRI atlas-based external beam radiation therapy treatment planning for prostate cancer

MICCAI'10 Proceedings of the 2010 international conference on Prostate cancer imaging: computer-aided diagnosis, prognosis, and intervention
Atlas based segmentation and mapping of organs at risk from planning CT for the development of voxel-wise predictive models of toxicity in prostate radiotherapy

MICCAI'10 Proceedings of the 2010 international conference on Prostate cancer imaging: computer-aided diagnosis, prognosis, and intervention
Computed tomography-based radiotherapy planning on the example of prostate cancer: application of level-set segmentation method guided by atlas-type knowledge

Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies

Quantified Score

Hi-index	0.00

Visualization

Abstract

A novel method of prostate segmentation in a new CT data making use of explicit knowledge about the prostate is proposed. The segmentation procedure is based on active shape statistical model (ASM) of the prostate, calculated using available data base of CTs annotated by medical doctors. In the paper the problem of automatic calculation of corresponding prostate landmarks in different CTs, which are absolutely necessary for the ASM, is solved in a new manner by: 1) finding parameters of affine and B-spline transformations in groupwise registration framework ensuring pixel-based registration of all available CTs in one common co-ordinate system, 2) performing forward affine and B-spline transformation of the annotated prostate contours into this co-ordinate system, 3) averaging them - interpolation & re-sampling, 4) propagation (projection) of mean landmarks, obtained in common co-ordinate system, to the training CTs using the backward transformation. Having the same prostate landmarks in set of CTs, the ASM of the prostate is calculated (its mean shape and tendencies to its direction variations). The result of matching ASM to the data is treated as the prostate segmentation result. Obtained results are presented and discussed in the paper.