A Unified 3D Framework for Organs-at-Risk Localization and Segmentation for Radiation Therapy Planning

Navarro F, Sasahara G, Shit S, Sekuboyina A, Ezhov I, Peeken JC, Combs SE, Menze BH (2022)

Publication Type: Conference contribution

Publication year: 2022

Journal

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society

Publisher: Institute of Electrical and Electronics Engineers Inc.

Book Volume: 2022-July

Pages Range: 1544-1547

Conference Proceedings Title: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Event location: Glasgow, GBR

ISBN: 9781728127828

DOI: 10.1109/EMBC48229.2022.9871680

Abstract

Automatic localization and segmentation of organs-at-risk (OAR) in CT are essential pre-processing steps in medical image analysis tasks, such as radiation therapy planning. For instance, the segmentation of OAR surrounding tumors enables the maximization of radiation to the tumor area without compromising the healthy tissues. However, the current medical workflow requires manual delineation of OAR, which is prone to errors and is annotator-dependent. In this work, we aim to introduce a unified 3D pipeline for OAR localization-segmentation rather than novel localization or segmentation architectures. To the best of our knowledge, our proposed framework fully enables the exploitation of 3D context information inherent in medical imaging. In the first step, a 3D multi-variate regression network predicts organs' centroids and bounding boxes. Secondly, 3D organ-specific segmentation networks are leveraged to generate a multi-organ segmentation map. Our method achieved an overall Dice score of 0.9260 ± 0.18% on the VISCERAL dataset containing CT scans with varying fields of view and multiple organs.

Involved external institutions

Technische Universität München (TUM) DE Germany (DE) University of Zurich / Universität Zürich (UZH) CH Switzerland (CH)

How to cite

APA:

Navarro, F., Sasahara, G., Shit, S., Sekuboyina, A., Ezhov, I., Peeken, J.C.,... Menze, B.H. (2022). A Unified 3D Framework for Organs-at-Risk Localization and Segmentation for Radiation Therapy Planning. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 1544-1547). Glasgow, GBR: Institute of Electrical and Electronics Engineers Inc..

MLA:

Navarro, Fernando, et al. "A Unified 3D Framework for Organs-at-Risk Localization and Segmentation for Radiation Therapy Planning." Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2022, Glasgow, GBR Institute of Electrical and Electronics Engineers Inc., 2022. 1544-1547.

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