From Local to Global Random Regression Forests: Exploring Anatomical Landmark Localization

Darko Stern, Thomas Ebner, Martin Urschler

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Abstract

State of the art anatomical landmark localization algorithms pair local Random Forest (RF) detection with disambiguation of locally similar structures by including high level knowledge about relative landmark locations. In this work we pursue the question, how much high-level knowledge is needed in addition to a single landmark localization RF to implicitly model the global configuration of multiple, potentially ambiguous landmarks. We further propose a novel RF localization algorithm that distinguishes locally similar structures by automatically identifying them, exploring the back-projection of the response from accurate local RF predictions. In our experiments we show that this approach achieves competitive results in single and multi-landmark localization when applied to 2D hand radiographic and 3D teeth MRI data sets. Additionally, when combined with a simple Markov Random Field model, we are able to outperform state of the art methods.
LanguageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention – MICCAI 2016
Subtitle of host publication19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II
EditorsSebastien Ourselin, Leo Joskowicz, Mert R. Sabuncu, Gozde Unal, William Wells
PublisherSpringer International Publishing AG
Pages221-229
Number of pages9
Volume9901
ISBN (Electronic)978-3-319-46723-8
ISBN (Print)978-3-319-46722-1
DOIs
StatusPublished - 21 Oct 2016
Event19th International Conference on Medical Image Computing & Computer Assisted Intervention - Intercontinental Athenaeum, Athens, Greece
Duration: 17 Oct 201621 Oct 2016
http://www.miccai2016.org

Publication series

NameLecture Notes in Computer Science
PublisherSpringer

Conference

Conference19th International Conference on Medical Image Computing & Computer Assisted Intervention
Abbreviated titleMICCAI
CountryGreece
CityAthens
Period17/10/1621/10/16
Internet address

Fingerprint

Magnetic resonance imaging
Experiments

Fields of Expertise

  • Information, Communication & Computing

Cooperations

  • BioTechMed-Graz

Cite this

Stern, D., Ebner, T., & Urschler, M. (2016). From Local to Global Random Regression Forests: Exploring Anatomical Landmark Localization. In S. Ourselin, L. Joskowicz, M. R. Sabuncu, G. Unal, & W. Wells (Eds.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016: 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II (Vol. 9901, pp. 221-229). (Lecture Notes in Computer Science). Springer International Publishing AG . https://doi.org/10.1007/978-3-319-46723-8_26

From Local to Global Random Regression Forests: Exploring Anatomical Landmark Localization. / Stern, Darko; Ebner, Thomas; Urschler, Martin.

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016: 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II. ed. / Sebastien Ourselin; Leo Joskowicz; Mert R. Sabuncu; Gozde Unal; William Wells. Vol. 9901 Springer International Publishing AG , 2016. p. 221-229 (Lecture Notes in Computer Science).

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Stern, D, Ebner, T & Urschler, M 2016, From Local to Global Random Regression Forests: Exploring Anatomical Landmark Localization. in S Ourselin, L Joskowicz, MR Sabuncu, G Unal & W Wells (eds), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016: 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II. vol. 9901, Lecture Notes in Computer Science, Springer International Publishing AG , pp. 221-229, 19th International Conference on Medical Image Computing & Computer Assisted Intervention, Athens, Greece, 17/10/16. https://doi.org/10.1007/978-3-319-46723-8_26
Stern D, Ebner T, Urschler M. From Local to Global Random Regression Forests: Exploring Anatomical Landmark Localization. In Ourselin S, Joskowicz L, Sabuncu MR, Unal G, Wells W, editors, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016: 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II. Vol. 9901. Springer International Publishing AG . 2016. p. 221-229. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-319-46723-8_26
Stern, Darko ; Ebner, Thomas ; Urschler, Martin. / From Local to Global Random Regression Forests: Exploring Anatomical Landmark Localization. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016: 19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part II. editor / Sebastien Ourselin ; Leo Joskowicz ; Mert R. Sabuncu ; Gozde Unal ; William Wells. Vol. 9901 Springer International Publishing AG , 2016. pp. 221-229 (Lecture Notes in Computer Science).
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