DYNAMIC REGISTRATION FOR GIGAPIXEL SERIAL WHOLE SLIDE IMAGES.

Autor:	Rossetti BJ; Department of Biomedical Informatics, Emory University, Atlanta, GA, 30322, USA., Wang F; Department of Computer Science, Stony Brook University, Stony Brook, NY, 11794, USA., Zhang P; Department of Computer Science, Stony Brook University, Stony Brook, NY, 11794, USA., Teodoro G; Department of Computer Science, University of Brasília, Brasília, DF, Brazil., Brat DJ; Department of Pathology, Emory University, Atlanta, GA, 30322, USA., Kong J; Department of Biomedical Informatics, Emory University, Atlanta, GA, 30322, USA.
Jazyk:	angličtina
Zdroj:	Proceedings. IEEE International Symposium on Biomedical Imaging [Proc IEEE Int Symp Biomed Imaging] 2017 Apr; Vol. 2017, pp. 424-428. Date of Electronic Publication: 2017 Jun 19.
DOI:	10.1109/ISBI.2017.7950552
Abstrakt:	High-throughput serial histology imaging provides a new avenue for the routine study of micro-anatomical structures in a 3D space. However, the emergence of serial whole slide imaging poses a new registration challenge, as the gigapixel image size precludes the direct application of conventional registration techniques. In this paper, we develop a three-stage registration with multi-resolution mapping and propagation method to dynamically produce registered subvolumes from serial whole slide images. We validate our algorithm with gigapixel images of serial brain tumor sections and synthetic image volumes. The qualitative and quantitative assessment results demonstrate the efficacy of our approach and suggest its promise for 3D histology reconstruction analysis.
Databáze:	MEDLINE
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