Scalable robust graph and feature extraction for arbitrary vessel networks in large volumetric datasets

Scalable robust graph and feature extraction for arbitrary vessel networks in large volumetric datasets

Abstract Background Recent advances in 3D imaging technologies provide novel insights to researchers and reveal finer and more detail of examined specimen, especially in the biomedical domain, but also impose huge challenges regarding scalability for automated analysis algorithms due to rapidly incr...

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Bibliographic Details
Main Authors: Dominik Drees, Aaron Scherzinger, René Hägerling, Friedemann Kiefer, Xiaoyi Jiang
Format: Article
Language:English
Published: BMC 2021-06-01
Series:BMC Bioinformatics
Subjects:
Graph extraction
Vessel network
Scalability
Large volume processing
Online Access:https://doi.org/10.1186/s12859-021-04262-w

Internet

https://doi.org/10.1186/s12859-021-04262-w

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