Atlas-based segmentation

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Abstract

Image segmentation is a main task in many medical applications such as surgical or radiation therapy planning, automatic labelling of anatomical structures or morphological and morphometrical studies. Segmentation in medical imaging is however challenging because of problems linked to low contrast images, fuzzy object-contours, similar intensities with adjacent objects of interest, etc. Using prior knowledge can help in the segmentation task. A widely used method consists to extract this prior knowledge from a reference image often called atlas. We review in this chapter the existing approaches for atlas-based segmentation in medical imaging and we focus on those based on a volume registration method.We present the problem of using atlas information for pathological image analysis and we propose our solution for atlas-based segmentation in MR image of the brain when large space-occupying lesions are present. Finally, we present the new research directions that aim at overcome current limitations of atlas-based segmentation approaches based on registration only.

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BachCuadra, M., Duay, V., & Thiran, J. P. H. (2015). Atlas-based segmentation. In Handbook of Biomedical Imaging: Methodologies and Clinical Research (pp. 221–244). Springer US. https://doi.org/10.1007/978-0-387-09749-7_12

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