Fully automated multi-modal anatomic atlas generation using 3D-slicer
Rackerseder J, González AML, Düwel C, Navab N, Frisch B (2017)
Publication Type: Conference contribution
Publication year: 2017
Journal
Publisher: Kluwer Academic Publishers
Pages Range: 306-311
Conference Proceedings Title: Informatik aktuell
Event location: Heidelberg, DEU
ISBN: 9783662543443
DOI: 10.1007/978-3-662-54345-0_69
Abstract
Atlases of the human body have many applications, including for instance the analysis of information from patient cohorts to evaluate the distribution of tumours and metastases. We present a 3D Slicer module that simplifies the task of generating a multi-modal atlas from anatomical and functional data. It provides for a simpler evaluation of existing image and verbose patient data by integrating a database that is automatically generated from text files and accompanies the visualization of the atlas volume. The computation of the atlas is a two step process. First, anatomical data is pairwise registered to a reference dataset with an affine initialization and a B-Spline based deformable approach. Second, the computed transformations are applied to anatomical as well as the corresponding functional data to generate both atlases. The module is validated with a publicly available soft tissue sarcoma dataset from The Cancer Imaging Archive. We show that functional data in the atlas volume correlates with the findings from the patient database.
Involved external institutions
Germany (DE)How to cite
APA:
Rackerseder, J., González, A.M.L., Düwel, C., Navab, N., & Frisch, B. (2017). Fully automated multi-modal anatomic atlas generation using 3D-slicer. In Klaus Hermann Maier-Hein, Heinz Handels, Thomas Martin Deserno, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 306-311). Heidelberg, DEU: Kluwer Academic Publishers.
MLA:
Rackerseder, Julia, et al. "Fully automated multi-modal anatomic atlas generation using 3D-slicer." Proceedings of the Workshops on Image processing for the medicine, 2017, Heidelberg, DEU Ed. Klaus Hermann Maier-Hein, Heinz Handels, Thomas Martin Deserno, Thomas Tolxdorff, Kluwer Academic Publishers, 2017. 306-311.
BibTeX: Download