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Mesh-Based Active Model Initialization for Multiple Organ Segmentation in MR Images

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Image Analysis and Recognition (ICIAR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10317))

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Abstract

Active models are widely used for segmentation of medical images. One of the key issues of active models is the initialization phase which affects significantly the segmentation performance. This paper presents a novel method for an automatic initialization of different types of active models by exploiting an adaptive mesh generation technique which is suitable for automatic detection of multiple organs. This method has been applied on MR images and results show the ability of the proposed method in simultaneously extracting initial approximate boundaries that are close to the exact boundaries of multiple organs. The effect of the proposed initialization algorithm on the segmentation has been tested on a series of arm and thoracic MR images and the results show an improvement in the convergence and speed of active model segmentation of multiple organs with respect to those obtained using manual initialization.

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Correspondence to M. R. Mohebpour .

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Mohebpour, M.R., Guibault, F., Cheriet, F. (2017). Mesh-Based Active Model Initialization for Multiple Organ Segmentation in MR Images. In: Karray, F., Campilho, A., Cheriet, F. (eds) Image Analysis and Recognition. ICIAR 2017. Lecture Notes in Computer Science(), vol 10317. Springer, Cham. https://doi.org/10.1007/978-3-319-59876-5_47

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  • DOI: https://doi.org/10.1007/978-3-319-59876-5_47

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  • Print ISBN: 978-3-319-59875-8

  • Online ISBN: 978-3-319-59876-5

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