title: Ultrasound image segmentation: a survey.
abstract: This paper reviews ultrasound segmentation paper methods, in a broad sense, focusing on techniques developed for medical B-mode ultrasound images. First, we present a review of articles by clinical application to highlight the approaches that have been investigated and degree of validation that has been done in different clinical domains. Then, we present a classification of methodology in terms of use of prior information. We conclude by selecting ten papers which have presented original ideas that have demonstrated particular clinical usefulness or potential specific to the ultrasound segmentation problem.
authors.affiliation: Department of Engineering Science, University of Oxford, UK. noble@robots.ox.ac.uk
authors.forename: J Alison
authors.initials: JA
authors.lastname: Noble
authors.forename: Djamal
authors.initials: D
authors.lastname: Boukerroui
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D016000:Cluster Analysis; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D010363:Pattern Recognition, Automated / Q000379:methods*; D014463:Ultrasonography / Q000379:methods*