Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: Joint 3-D vessel segmentation and centerline extraction using oblique Hough forests with steerable filters
Authors: Schneider, Matthias
Hirsch, Sven
Weber, Bruno
Székely, Gábor
Menze, Bjoern H.
DOI: 10.1016/
Published in: Medical Image Analysis
Volume(Issue): 19
Issue: 1
Page(s): 220
Pages to: 249
Issue Date: 2015
Publisher / Ed. Institution: Elsevier
ISSN: 1361-8415
Language: English
Subjects: Centerline extraction; Multivariate Hough voting; Oblique random forest; Steerable filters; Vessel segmentation; Algorithms
Subject (DDC): 610: Medicine and health
Abstract: We propose a novel framework for joint 3-D vessel segmentation and centerline extraction. The approach is based on multivariate Hough voting and oblique random forests (RFs) that we learn from noisy annotations. It relies on steerable filters for the efficient computation of local image features at different scales and orientations.
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: Life Sciences and Facility Management
Organisational Unit: Institute of Computational Life Sciences (ICLS)
Appears in collections:Publikationen Life Sciences und Facility Management

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