Anatomical structures and tissues are often hard to be segmented in medical images due to their poorly defined\nboundaries, i.e., low contrast in relation to other nearby false boundaries. The specification of the boundary polarity\ncan help alleviate a part of this problem. In this work, we discuss how to incorporate this property in the relative fuzzy\nconnectedness (RFC) framework. We include a theoretical proof of the optimality of the new algorithm, named\noriented relative fuzzy connectedness (ORFC), in terms of an oriented energy function subject to the seed constraints,\nand show its usage to devise powerful hybrid image segmentation methods. The methods are evaluated using\nmedical images of MRI and CT of the human brain and thoracic studies.
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