title: Phase symmetry approach applied to children heart chambers segmentation: a comparative study.
abstract: Segmentation of echocardiographic images presents a great challenge because these images contain strong speckle noise and artifacts. Besides, most ultrasound segmentation methods are semi-automatic, requiring initial contour to be manually identified in the images. In this work, we propose an algorithm based on the phase symmetry approach and level set evolution, in order to extract simultaneously all heart cavities in a fully automatic way. The level set evolution uses a new logarithmic based stopping function, which demonstrates to perform well in the boundary extraction. We compared our method with other level set approaches, the watershed technique, and the manual segmentation made by two physicians. The experimental work was based on echocardiography images of children. Similarity metrics, namely Pratt Function, Pixel Mean Error, and Similarity Angle have been used for the performance evaluation of the different methods. The results indicate that our method has a performance at least 4% superior to the other methods able to segment the four chambers. Even for the two worst boundary extraction cases (right ventricle and left atrium) the performance of the proposed method still is better than the other techniques.
authors.forename: Sofia G
authors.initials: SG
authors.lastname: Antunes
authors.forename: José Silvestre
authors.initials: JS
authors.lastname: Silva
authors.forename: Jaime B
authors.initials: JB
authors.lastname: Santos
authors.forename: Paula
authors.initials: P
authors.lastname: Martins
authors.forename: Eduardo
authors.initials: E
authors.lastname: Castela
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D002648:Child; D002675:Child, Preschool; D004452:Echocardiography / Q000379:methods*; D006325:Heart Atria / Q000000981:diagnostic imaging*; D006352:Heart Ventricles / Q000000981:diagnostic imaging*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007223:Infant; D007231:Infant, Newborn; D010363:Pattern Recognition, Automated / Q000379:methods*; D012680:Sensitivity and Specificity