title: Ultrasound image segmentation using spectral clustering.
abstract: Segmentation of ultrasound images is necessary in a variety of clinical applications, but the development of automatic techniques is still an open problem. Spectral clustering techniques have recently become popular for data and image analysis. In particular, image segmentation has been proposed via the normalized cut (NCut) criterion. This article describes an initial investigation to determine the suitability of such segmentation techniques for ultrasound images. The adaptation of the NCut technique to ultrasound is described first. Segmentation is then performed on simulated ultrasound images. Tests are also performed on abdominal and fetal images with the segmentation results compared to manual segmentation. The success of the segmentation on these test cases warrants further research into NCut-based segmentation of ultrasound images.
authors.affiliation: Harvard Medical School, Brigham and Women's Hospital, Boston, MA 02115, USA. narchip@bwh.harvard.edu
authors.forename: Neculai
authors.initials: N
authors.lastname: Archip
authors.forename: Robert
authors.initials: R
authors.lastname: Rohling
authors.forename: Peter
authors.initials: P
authors.lastname: Cooperberg
authors.forename: Hamid
authors.initials: H
authors.lastname: Tahmasebpour
mesh_terms: D003198:Computer Simulation; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D012815:Signal Processing, Computer-Assisted; D014463:Ultrasonography / Q000379:methods*