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MR prior based automatic segmentation of the prostate in TRUS images for MR/TRUS data fusion
- Source :
- Proceedings of the IEEE International Symposium on Biomedical Imaging, IEEE International Symposium on Biomedical Imaging, ISBI'2010, IEEE International Symposium on Biomedical Imaging, ISBI'2010, Apr 2010, Rotterdam, Netherlands. pp.640-643, ISBI
- Publication Year :
- 2010
- Publisher :
- HAL CCSD, 2010.
-
Abstract
- International audience; The poor signal-to-noise ratio in transrectal ultrasound (TRUS) images makes the fully automatic segmentation of the prostate challenging and most approaches proposed in the literature still lack robustness and accuracy. However, it is relatively straightforward to obtain high quality segmentations in magnetic resonance (MR) images. In the context of MR to TRUS data fusion the information gathered in the MR images can hence provide a strong prior for US segmentation. In this paper, we describe a method to non-linearly register a patient specific mesh of the prostate build from MR images to TRUS volume. The MR prior provides shape and volume constraints that are used to guide the MR-to-TRUS surface deformation, in collaboration with a US image contour appearance model. The anatomical point correspondences between the MR and TRUS surfaces are obtained implicitly. The method was validated on 30 pairs of MR/TRUS patient exams and achieves a mean Dice value 0.85 and a mean surface error of 2.0 mm.
- Subjects :
- [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging
[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]
Image registration
02 engineering and technology
030218 nuclear medicine & medical imaging
03 medical and health sciences
0302 clinical medicine
Prostate
registration
0202 electrical engineering, electronic engineering, information engineering
medicine
magnetic resonance imaging
Segmentation
Computer vision
Image fusion
business.industry
ultrasound
segmentation
Image segmentation
Sensor fusion
[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]
medicine.anatomical_structure
[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging
Fully automatic
Automatic segmentation
020201 artificial intelligence & image processing
Artificial intelligence
business
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Proceedings of the IEEE International Symposium on Biomedical Imaging, IEEE International Symposium on Biomedical Imaging, ISBI'2010, IEEE International Symposium on Biomedical Imaging, ISBI'2010, Apr 2010, Rotterdam, Netherlands. pp.640-643, ISBI
- Accession number :
- edsair.doi.dedup.....3e45da54b143ea68a30205339bf959ab