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Stitching pathological tissue images using DOP feature tracking

: Bergler, M.; Weiherer, M.; Bergen, T.; Avenhaus, M.; Rauber, D.; Wittenberg, T.; Münzenmayer, C.; Benz, M.


Maier, A.:
Bildverarbeitung für die Medizin 2018 : Algorithmen - Systeme - Anwendungen : Proceedings des Workshops vom 11. bis 13. März 2018 in Erlangen
Berlin: Springer, 2018 (Informatik aktuell)
ISBN: 978-3-662-56537-7 (online)
ISBN: 978-3-662-56536-0
Workshop Bildverarbeitung für die Medizin (BVM) <2018, Erlangen>
Conference Paper
Fraunhofer IIS ()

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.