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Evolutionary improved object detector for ultrasound images | IEEE Conference Publication | IEEE Xplore

Evolutionary improved object detector for ultrasound images


Abstract:

Object detection in ultrasound images is difficult problem mainly because of relatively low signal-to-noise ratio. This paper deals with object detection in the noisy ult...Show More

Abstract:

Object detection in ultrasound images is difficult problem mainly because of relatively low signal-to-noise ratio. This paper deals with object detection in the noisy ultrasound images using modified version of Viola-Jones object detector. The method describes detection of carotid artery longitudinal section in ultrasound B-mode images. The detector is primarily trained by AdaBoost algorithm and uses a cascade of Haar-like features as a classifier. The main contribution of this paper is a method for detection of carotid artery longitudinal section. This method creates cascade of classifiers automatically using genetic algorithms. We also created post-processing method that marks position of artery in the image. The proposed method was released as open-source software. Resulting detector achieved accuracy 96.29%. When compared to SVM classification enlarged with RANSAC (RANdom SAmple Consensus) method that was used for detection of carotid artery longitudinal section, works our method real-time.
Date of Conference: 02-04 July 2013
Date Added to IEEE Xplore: 30 September 2013
ISBN Information:
Conference Location: Rome, Italy

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