Oriented relative fuzzy connectedness: theory, algorithms, and its applications in hybrid image segmentation methods

Autor(es)

Ccacyahuillca Bejar, Hans Harley ^[1] ; Miranda, Paulo Av ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Dept Comp Sci, BR-05508090 Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING; JUL 23 2015.
• Citações Web of Science: 7

Resumo

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

• Processo FAPESP: 11/50761-2 - Modelos e métodos de e-Science para ciências da vida e agrárias
• Beneficiário: Roberto Marcondes Cesar Junior
• Linha de fomento: Auxílio à Pesquisa - Temático