Literature DB >> 12582978

Automatic 3D registration for interventional MRI-guided treatment of prostate cancer.

Baowei Fei1, Jeffrey L Duerk, David L Wilson.   

Abstract

The goal of this research is to register real-time interventional magnetic resonance imaging (iMRI) slice images with a previously obtained high-resolution MRI image volume, which in turn can be registered with functional images such as those from SPECT. The immediate application is in iMRI-guided treatment of prostate cancer, where additional images are desired to improve tumor targeting. In this article, simulation experiments are performed to demonstrate the feasibility of slice-to-volume registration for this application. We acquired 3D volume images from a 1.5-T MRI system and simulated low-field iMRI image slices by creating thick slices and adding noise. We created a slice-to-volume mutual information registration algorithm with special features to improve robustness. Features included a multiresolution approach, two similarity measures, and automatic restarting to avoid local minima. To assess the quality of registration, we calculated 3D displacements on a voxel-by-voxel basis over a volume of interest between slice-to-volume registration and volume-to-volume registration, which was previously shown to be quite accurate. More than 800 registration experiments were performed on MR images of three volunteers. The slice-to-volume registration algorithm was very robust and accurate for transverse slice images covering the prostate, with a registration error of only 0.4 +/- 0.2 mm. Error was greater at other slice orientations and positions. The automatic slice-to-volume mutual information registration algorithm is robust and probably sufficiently accurate to aid in iMRI-guided treatment of prostate cancer. Copyright 2003 Wiley-Liss, Inc.

Entities:  

Mesh:

Year:  2002        PMID: 12582978     DOI: 10.1002/igs.10052

Source DB:  PubMed          Journal:  Comput Aided Surg        ISSN: 1092-9088


  20 in total

1.  3D Prostate Segmentation of Ultrasound Images Combining Longitudinal Image Registration and Machine Learning.

Authors:  Xiaofeng Yang; Baowei Fei
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2012-02-23

2.  PROBABILISTIC NON-RIGID REGISTRATION OF PROSTATE IMAGES: MODELING AND QUANTIFYING UNCERTAINTY.

Authors:  Petter Risholm; Andriy Fedorov; Jennifer Pursley; Kemal Tuncali; Robert Cormack; William M Wells
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2011-06-09

3.  Computer-aided diagnosis of prostate cancer with MRI.

Authors:  Baowei Fei
Journal:  Curr Opin Biomed Eng       Date:  2017-09

4.  Automatic registration of CT volumes and dual-energy digital radiography for detection of cardiac and lung diseases.

Authors:  Baowei Fei; Xiang Chen; Hesheng Wang; John M Sabol; Elena DuPont; Robert C Gilkeson
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2006

5.  Automatic 3D-to-2D registration for CT and dual-energy digital radiography for calcification detection.

Authors:  Xiang Chen; Robert C Gilkeson; Baowei Fei
Journal:  Med Phys       Date:  2007-12       Impact factor: 4.071

Review 6.  MR-guided prostate interventions.

Authors:  Clare Tempany; Sarah Straus; Nobuhiko Hata; Steven Haker
Journal:  J Magn Reson Imaging       Date:  2008-02       Impact factor: 4.813

7.  A Molecular Image-directed, 3D Ultrasound-guided Biopsy System for the Prostate.

Authors:  Baowei Fei; David M Schuster; Viraj Master; Hamed Akbari; Aaron Fenster; Peter Nieh
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2012-02-16

8.  Automatic Intensity-based 3D-to-2D Registration of CT Volume and Dual-energy Digital Radiography for the Detection of Cardiac Calcification.

Authors:  Xiang Chen; Robert Gilkeson; Baowei Fei
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2007-03-03

9.  Accuracy Evaluation of a 3D Ultrasound-guided Biopsy System.

Authors:  Walter J Wooten; Jonathan A Nye; David M Schuster; Peter T Nieh; Viraj A Master; John R Votaw; Baowei Fei
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2013-03-14

10.  Learning statistical correlation for fast prostate registration in image-guided radiotherapy.

Authors:  Yonghong Shi; Shu Liao; Dinggang Shen
Journal:  Med Phys       Date:  2011-11       Impact factor: 4.071

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