Visualizing anatomical labels on brain images: developing a multi-functional display method

  • This work describes a novel software tool for visualizing anatomical segmentations of medical images. It was developed as part of a bachelor's thesis project, with a view to supporting research into automatic anatomical brain image segmentation. The tool builds on a widely-used visualization approach for 3D image volumes, where sections in orthogonal directions are rendered on screen as 2D images. It implements novel display modes that solve common problems with conventional viewer programs. In particular, it features a double-contour display mode to aid the user's spatial orientation in the image, as well as modes for comparing two competing segmentation labels pertaining to one and the same anatomical region. The tool was developed as an extension to an existing open-source software suite for medical image processing. The visualizationThis work describes a novel software tool for visualizing anatomical segmentations of medical images. It was developed as part of a bachelor's thesis project, with a view to supporting research into automatic anatomical brain image segmentation. The tool builds on a widely-used visualization approach for 3D image volumes, where sections in orthogonal directions are rendered on screen as 2D images. It implements novel display modes that solve common problems with conventional viewer programs. In particular, it features a double-contour display mode to aid the user's spatial orientation in the image, as well as modes for comparing two competing segmentation labels pertaining to one and the same anatomical region. The tool was developed as an extension to an existing open-source software suite for medical image processing. The visualization modes are, however, suitable for implementation in the context of other viewer programs that follow a similar rendering approach. The modified code can be found here: soundray.org/mm-segmentation-visualization.tar.gz.show moreshow less

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Author:Marius Meyer
URN:urn:nbn:de:kola-18015
Referee:Kai Lawonn, Rolf A. Heckemann
Advisor:Kai Lawonn
Document Type:Bachelor Thesis
Language:English
Date of Publication (online):2019/03/03
Date of first Publication:2019/03/15
Publishing Institution:Universität Koblenz, Universitätsbibliothek
Granting Institution:Universität Koblenz, Fachbereich 4
Date of final exam:2018/09/03
Release Date:2019/03/15
Page Number:i, 15
Institutes:Fachbereich 4 / Institut für Computervisualistik
Licence (German):Es gilt das deutsche Urheberrecht: § 53 UrhG
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