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Slice correspondence estimation using SURF descriptors and context-based search for prostate whole-mount histology MRI registration.
- Source :
-
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2016 Aug; Vol. 2016, pp. 1163-1166. - Publication Year :
- 2016
-
Abstract
- Registration of histopathology volumes to Magnetic Resonance Images(MRI) is a crucial step for finding correlations in Prostate Cancer (PCa) and assessing tumor agressivity. This paper proposes a two-stage framework aimed at registering both modalities. Firstly, Speeded-Up Robust Features (SURF) algorithm and a context-based search is used to automatically determine slice correspondences between MRI and histology volumes. This step initializes a multimodal nonrigid registration strategy, which allows to propagate histology slices to MRI. Evaluation was performed on 5 prospective studies using a slice index score and landmark distances. With respect to a manual ground truth, the first stage of the framework exhibited an average error of 1,54 slice index and 3,51 mm in the prostate specimen. The reconstruction of a three-dimensional Whole-Mount Histology (WMH) shows promising results aimed to perform later PCa pattern detection and staging.
Details
- Language :
- English
- ISSN :
- 2694-0604
- Volume :
- 2016
- Database :
- MEDLINE
- Journal :
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
- Publication Type :
- Academic Journal
- Accession number :
- 28268532
- Full Text :
- https://doi.org/10.1109/EMBC.2016.7590911