Shachar Avni
Graduate student (Masters)
School of Computing
Queen's University
Avni, Shachar; Vikal, Siddharth; Fichtinger, Gabor
Design of a predictive targeting error simulator for MRI-guided prostate biopsy Conference
Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling, SPIE SPIE, San Diego, California, USA, 2010, ISBN: 0277-786X.
@conference{Avni2010,
title = {Design of a predictive targeting error simulator for MRI-guided prostate biopsy},
author = {Shachar Avni and Siddharth Vikal and Gabor Fichtinger},
url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Avni2010.pdf},
doi = {http://dx.doi.org/10.1117/12.844476},
isbn = {0277-786X},
year = {2010},
date = {2010-01-01},
urldate = {2010-01-01},
booktitle = {Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling},
pages = {76251A-1 - 76251A-8},
publisher = {SPIE},
address = {San Diego, California, USA},
organization = {SPIE},
abstract = {<p>Multi-parametric MRI is a new imaging modality superior in quality to Ultrasound (US) which is currently used in standard prostate biopsy procedures. Surface-based registration of the pre-operative and intra-operative prostate volumes is a simple alternative to side-step the challenges involved with deformable registration. However, segmentation errors inevitably introduced during prostate contouring spoil the registration and biopsy targeting accuracies. For the crucial purpose of validating this procedure, we introduce a fully interactive and customizable simulator which determines the resulting targeting errors of simulated registrations between prostate volumes given user-provided parameters for organ deformation, segmentation, and targeting. We present the workflow executed by the simulator in detail and discuss the parameters involved. We also present a segmentation error introduction algorithm, based on polar curves and natural cubic spline interpolation, which introduces statistically realistic contouring errors. One simulation, including all I/O and preparation for rendering, takes approximately 1 minute and 40 seconds to complete on a system with 3 GB of RAM and four Intel Core 2 Quad CPUs each with a speed of 2.40 GHz. Preliminary results of our simulation suggest the maximum tolerable segmentation error given the presence of a 5.0 mm wide small tumor is between 4-5 mm. We intend to validate these results via clinical trials as part of our ongoing work.</p>},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
<p>Multi-parametric MRI is a new imaging modality superior in quality to Ultrasound (US) which is currently used in standard prostate biopsy procedures. Surface-based registration of the pre-operative and intra-operative prostate volumes is a simple alternative to side-step the challenges involved with deformable registration. However, segmentation errors inevitably introduced during prostate contouring spoil the registration and biopsy targeting accuracies. For the crucial purpose of validating this procedure, we introduce a fully interactive and customizable simulator which determines the resulting targeting errors of simulated registrations between prostate volumes given user-provided parameters for organ deformation, segmentation, and targeting. We present the workflow executed by the simulator in detail and discuss the parameters involved. We also present a segmentation error introduction algorithm, based on polar curves and natural cubic spline interpolation, which introduces statistically realistic contouring errors. One simulation, including all I/O and preparation for rendering, takes approximately 1 minute and 40 seconds to complete on a system with 3 GB of RAM and four Intel Core 2 Quad CPUs each with a speed of 2.40 GHz. Preliminary results of our simulation suggest the maximum tolerable segmentation error given the presence of a 5.0 mm wide small tumor is between 4-5 mm. We intend to validate these results via clinical trials as part of our ongoing work.</p>
Lasso, Andras; Avni, Shachar; Fichtinger, Gabor
Targeting Error Simulator for Image-guided Prostate Needle Placement Conference
EMBC2010 - 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Buenos Aires, Argentina, 2010.
@conference{Lasso2010b,
title = {Targeting Error Simulator for Image-guided Prostate Needle Placement},
author = {Andras Lasso and Shachar Avni and Gabor Fichtinger},
url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Lasso2010b.pdf},
year = {2010},
date = {2010-01-01},
urldate = {2010-01-01},
booktitle = {EMBC2010 - 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
pages = {5424-5427},
address = {Buenos Aires, Argentina},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Lasso, Andras; Avni, Shachar; Fichtinger, Gabor
Targeting error simulator for image-guided prostate needle placement Journal Article
In: pp. 5424-5427, 2010.
@article{fichtinger2010q,
title = {Targeting error simulator for image-guided prostate needle placement},
author = {Andras Lasso and Shachar Avni and Gabor Fichtinger},
url = {https://ieeexplore.ieee.org/abstract/document/5626494/},
year = {2010},
date = {2010-01-01},
pages = {5424-5427},
publisher = {IEEE},
abstract = {Motivation
Needle-based biopsy and local therapy of prostate cancer depend multimodal imaging for both target planning and needle guidance. The clinical process involves selection of target locations in a pre-operative image volume and registering these to an intra-operative volume. Registration inaccuracies inevitably lead to targeting error, a major clinical concern. The analysis of targeting error requires a large number of images with known ground truth, which has been infeasible even for the largest research centers.
Methods
We propose to generate realistic prostate imaging data in a controllable way, with known ground truth, by simulation of prostate size, shape, motion and deformation typically encountered in prostatic needle placement. This data is then used to evaluate a given registration algorithm, by testing its ability to reproduce ground truth contours, motions and deformations. The method builds on …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Motivation
Needle-based biopsy and local therapy of prostate cancer depend multimodal imaging for both target planning and needle guidance. The clinical process involves selection of target locations in a pre-operative image volume and registering these to an intra-operative volume. Registration inaccuracies inevitably lead to targeting error, a major clinical concern. The analysis of targeting error requires a large number of images with known ground truth, which has been infeasible even for the largest research centers.
Methods
We propose to generate realistic prostate imaging data in a controllable way, with known ground truth, by simulation of prostate size, shape, motion and deformation typically encountered in prostatic needle placement. This data is then used to evaluate a given registration algorithm, by testing its ability to reproduce ground truth contours, motions and deformations. The method builds on …
Needle-based biopsy and local therapy of prostate cancer depend multimodal imaging for both target planning and needle guidance. The clinical process involves selection of target locations in a pre-operative image volume and registering these to an intra-operative volume. Registration inaccuracies inevitably lead to targeting error, a major clinical concern. The analysis of targeting error requires a large number of images with known ground truth, which has been infeasible even for the largest research centers.
Methods
We propose to generate realistic prostate imaging data in a controllable way, with known ground truth, by simulation of prostate size, shape, motion and deformation typically encountered in prostatic needle placement. This data is then used to evaluate a given registration algorithm, by testing its ability to reproduce ground truth contours, motions and deformations. The method builds on …