Abstract

Carotid Artery (CA) is one of the vital organs in the human body. CA features that can be used are position, size and volume. Position feature can used to determine the preliminary initialization of the tracking. Examination of the CA features can use Ultrasound. Ultrasound imaging can be operated dependently by an skilled operator, hence there could be some differences in the images result obtained by two or more different operators. This can affect the process of determining of CA. To reduce the level of subjectivity among operators, it can determine the position of the CA automatically. In this study, the proposed method is to segment CA in B-Mode Ultrasound Image based on morphology, geometry and gradient direction. This study consists of three steps, the data collection, preprocessing and artery segmentation. The data used in this study were taken directly by the researchers and taken from the Brno university's signal processing lab database. Each data set contains 100 carotid artery B-Mode ultrasound image. Artery is modeled using ellipse with center c, major axis a and minor axis b. The proposed method has a high value on each data set, 97% (data set 1), 73 % (data set 2), 87% (data set 3). This segmentation results will then be used in the process of tracking the CA.

Original languageEnglish
Title of host publicationSecond International Workshop on Pattern Recognition
EditorsGuojian Chen, Xudong Jiang, Masayuki Arai
PublisherSPIE
ISBN (Electronic)9781510613508
DOIs
Publication statusPublished - 2017
Event2nd International Workshop on Pattern Recognition, IWPR 2017 - Singapore, Singapore
Duration: 1 May 20173 May 2017

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10443
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference2nd International Workshop on Pattern Recognition, IWPR 2017
Country/TerritorySingapore
CitySingapore
Period1/05/173/05/17

Keywords

  • Carotid artery
  • Gradient direction
  • Morphology
  • Segmentation
  • Ultrasound image

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