Stitching Pathological Tissue Images using DOP Feature Tracking
Bergler M, Weiherer M, Bergen T, Avenhaus M, Rauber D, Wittenberg T, Münzenmayer C, Benz M (2018)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2018
Publisher: Springer Berlin Heidelberg
City/Town: Berlin, Heidelberg
Pages Range: 322--327
Conference Proceedings Title: Bildverarbeitung für die Medizin 2018
Event location: Erlangen
ISBN: 978-3-662-56537-7
DOI: 10.1007/978-3-662-56537-7_84
Abstract
This contribution introduces an approach for stitching multiple images of a histological slide to a panorama image using Differences of Paraboloids (DOP). DOP provides a novel method for the detection, description and matching of features of two overlapping images. In our context of manual whole-slide imaging (WSI), DOP extracts essential keypoints of an image and describes them with feature vectors considering the keypoint's neighborhood. The DOP feature vector of the current image is then matched against the feature vectors of all previous images. With matching correspondences, a feature based image registration is generated that estimates the translation between two overlapping images. Likewise, all images are aligned to form a whole-slide panorama. Our results reveal a superior stitching quality employing the presented DOP approach in comparison to the well-known SIFT and SURF. Our evaluation is based on the homogeneity at the artifically created edges in the panorama due to the stitching. The DOP offers a convincing solution to stitch pathological tissue.
Authors with CRIS profile
Matthias Bergler
Chair of Visual Computing (LGDV)
Malte Avenhaus
Thomas Wittenberg
Technische Fakultät
Involved external institutions
Germany (DE)How to cite
APA:
Bergler, M., Weiherer, M., Bergen, T., Avenhaus, M., Rauber, D., Wittenberg, T.,... Benz, M. (2018). Stitching Pathological Tissue Images using DOP Feature Tracking. In Maier A, Deserno TM, Handels H, Maier-Hein KH, Palm C, Tolxdorff T (Eds.), Bildverarbeitung für die Medizin 2018 (pp. 322--327). Erlangen: Berlin, Heidelberg: Springer Berlin Heidelberg.
MLA:
Bergler, Matthias, et al. "Stitching Pathological Tissue Images using DOP Feature Tracking." Proceedings of the Bildverarbeitung für die Medizin, Erlangen Ed. Maier A, Deserno TM, Handels H, Maier-Hein KH, Palm C, Tolxdorff T, Berlin, Heidelberg: Springer Berlin Heidelberg, 2018. 322--327.
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