Registration of in vivo prostate magnetic resonance images to digital histopathology images

Authors:
A. D. Ward;C. Crukley;C. McKenzie;J. Montreuil;E. Gibson;J. A. Gomez;M. Moussa;G. Bauman;A. Fenster
Affiliations:
Robarts Research Institute;Lawson Health Research Institute, London, Ontario, Canada;Robarts Research Institute and Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada and Lawson Health Research Institute, London, Ontario, Canada;Robarts Research Institute;Robarts Research Institute and Biomedical Engineering Graduate Program, The University of Western Ontario, London, Ontario, Canada;Department of Pathology, The University of Western Ontario, London, Ontario, Canada;Department of Pathology, The University of Western Ontario, London, Ontario, Canada;Department of Oncology, The University of Western Ontario, London, Ontario, Canada;Robarts Research Institute and Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada and Lawson Health Research Institute, London, Ontario, Canada
Venue:
MICCAI'10 Proceedings of the 2010 international conference on Prostate cancer imaging: computer-aided diagnosis, prognosis, and intervention
Year:
2010

Citing 2
Cited 1

Principal Warps: Thin-Plate Splines and the Decomposition of Deformations

IEEE Transactions on Pattern Analysis and Machine Intelligence
Block Matching: A General Framework to Improve Robustness of Rigid Registration of Medical Images

MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention

Validation of direct registration of whole-mount prostate digital histopathology to ex vivo MR images

MICCAI'11 Proceedings of the 2011 international conference on Prostate cancer imaging: image analysis and image-guided interventions

Quantified Score

Hi-index	0.00

Visualization

Abstract

Early and accurate diagnosis of prostate cancer enables minimally invasive therapies to cure the cancer with less morbidity. The purpose of this work is to non-rigidly register in vivo pre-prostatectomy prostate medical images to regionally-graded histopathology images from post-prostatectomy specimens, seeking a relationship between the multi parametric imaging and cancer distribution and aggressiveness. Our approach uses image-based registration in combination with a magnetically tracked probe to orient the physical slicing of the specimen to be parallel to the in vivo imaging planes, yielding a tractable 2D registration problem. We measured a target registration error of 0.85 mm, a mean slicing plane marking error of 0.7 mm, and a mean slicing error of 0.6 mm; these results compare favourably with our 2.2 mm diagnostic MR image thickness. Qualitative evaluation of in vivo imaging-histopathology fusion reveals excellent anatomic concordance between MR and digital histopathology.