NDLI: Boundary delineation for hepatic hemangioma in ultrasound images

Content Provider	IEEE Xplore Digital Library
Author	Bahrami, N. Rezatofighi, S.H. Adeli, A.M. Setarehdan, S.K.
Copyright Year	2011
Description	Author affiliation: Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran (Bahrami, N.; Rezatofighi, S.H.; Adeli, A.M.; Setarehdan, S.K.)
Abstract	Hemangioma is one of the most common benign congenital complications of the human body which can arise in interior organs and external limbs. The main aim of this work is to present a new method for automatic detection of liver hemangioma and its boundaries in ultrasound images, using image processing techniques. Overall there are two phases, the preprocessing procedure and the boundary delineation phase. The preprocessing phase includes three main stages: 1. Image contrast enhancement using Difference of Offset Gaussian (DoOG) method, 2. Applying Canny edge filtering, 3. Applying an adaptive threshold in order to detect the ROI (hemangioma). Following, the snake algorithm is used to segment the hemangioma region in the second phase. For the quantitative assessment of the proposed method for the segmentation stage, the results derived via the proposed algorithms have been compared with the corresponding segmented regions determined by an expert using three similarity criteria. The results showed 73 percent similarity without pre-processing and 90 percent similarity with pre-processing.
Starting Page	7989
Ending Page	7992
File Size	556607
Page Count	4
File Format	PDF
ISBN	9781424441211
ISSN	1557170X
e-ISBN	9781457715891
e-ISBN	9781424441228
DOI	10.1109/IEMBS.2011.6091970
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Ultrasonic imaging Image segmentation Image edge detection Measurement Filtering algorithms Noise Liver Ultrasound Active contour model Difference of offset Gaussian Hemangioma Image processing
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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