Display Settings:

Format

Send to:

Choose Destination
See comment in PubMed Commons below
Comput Med Imaging Graph. 2011 Oct-Dec;35(7-8):568-78. doi: 10.1016/j.compmedimag.2010.12.003. Epub 2011 Jan 21.

Determining histology-MRI slice correspondences for defining MRI-based disease signatures of prostate cancer.

Author information

  • 1Department of Biomedical Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA. gyxiao@rci.rutgers.edu

Abstract

Mapping the spatial disease extent in a certain anatomical organ/tissue from histology images to radiological images is important in defining the disease signature in the radiological images. One such scenario is in the context of men with prostate cancer who have had pre-operative magnetic resonance imaging (MRI) before radical prostatectomy. For these cases, the prostate cancer extent from ex vivo whole-mount histology is to be mapped to in vivo MRI. The need for determining radiology-image-based disease signatures is important for (a) training radiologist residents and (b) for constructing an MRI-based computer aided diagnosis (CAD) system for disease detection in vivo. However, a prerequisite for this data mapping is the determination of slice correspondences (i.e. indices of each pair of corresponding image slices) between histological and magnetic resonance images. The explicit determination of such slice correspondences is especially indispensable when an accurate 3D reconstruction of the histological volume cannot be achieved because of (a) the limited tissue slices with unknown inter-slice spacing, and (b) obvious histological image artifacts (tissue loss or distortion). In the clinic practice, the histology-MRI slice correspondences are often determined visually by experienced radiologists and pathologists working in unison, but this procedure is laborious and time-consuming. We present an iterative method to automatically determine slice correspondence between images from histology and MRI via a group-wise comparison scheme, followed by 2D and 3D registration. The image slice correspondences obtained using our method were compared with the ground truth correspondences determined via consensus of multiple experts over a total of 23 patient studies. In most instances, the results of our method were very close to the results obtained via visual inspection by these experts.

Copyright © 2010 Elsevier Ltd. All rights reserved.

PMID:
21255974
[PubMed - indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Icon for Elsevier Science
    Loading ...
    Write to the Help Desk