Segmentation of prostate from  CT scans using a combined voxel random forests classification with spherical harmonics regularization

F. Commandeur; O. Acosta; A. Simon; J. D. Ospina Arango; J. L. Dillenseger; R. Mathieu; P. Haigron; R. de Crevoisier

doi:10.1117/12.2073489

28 January 2015 Segmentation of prostate from CT scans using a combined voxel random forests classification with spherical harmonics regularization

F. Commandeur, O. Acosta, A. Simon, J. D. Ospina Arango, J. L. Dillenseger, R. Mathieu, P. Haigron, R. de Crevoisier

Author Affiliations +

Proceedings Volume 9287, 10th International Symposium on Medical Information Processing and Analysis; 92870F (2015) https://doi.org/10.1117/12.2073489
Event: Tenth International Symposium on Medical Information Processing and Analysis, 2014, Cartagena de Indias, Colombia

Abstract

In prostate cancer external beam radiotherapy, pelvic structures identification in computed tomography (CT) is required for the treatment planning and is performed manually by experts. Prostate manual delineations in CT modality is time consuming and prone to observer variability. We propose a fully automated process using a combination of a Random Forests (RF) classification and Spherical Harmonics (SPHARM) to identify the prostate boundaries. The proposed method outperformed classical atlas based approach from the literature. Combining RF to detect the prostate and SPHARM for shape regularization provided promising results for automatic prostate segmentation.

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F. Commandeur, O. Acosta, A. Simon, J. D. Ospina Arango, J. L. Dillenseger, R. Mathieu, P. Haigron, and R. de Crevoisier "Segmentation of prostate from CT scans using a combined voxel random forests classification with spherical harmonics regularization", Proc. SPIE 9287, 10th International Symposium on Medical Information Processing and Analysis, 92870F (28 January 2015); https://doi.org/10.1117/12.2073489

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