DocumentCode :
2505461
Title :
Boundary delineation for hepatic hemangioma in ultrasound images
Author :
Bahrami, Naeim ; Rezatofighi, Seyed Hamid ; Adeli, Aliyeh Mahdavi ; Setarehdan, S. Kamaledin
Author_Institution :
Control & Intell. Process. Center of Excellence, Univ. of Tehran, Tehran, Iran
fYear :
2011
fDate :
Aug. 30 2011-Sept. 3 2011
Firstpage :
7989
Lastpage :
7992
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.
Keywords :
biomedical ultrasonics; blood vessels; cancer; edge detection; image enhancement; image segmentation; liver; medical image processing; Canny edge filtering; automatic detection; boundary delineation; boundary delineation phase; difference of offset Gaussian method; hepatic hemangioma; image contrast enhancement; image processing; preprocessing phase; snake algorithm; ultrasound images; Filtering algorithms; Image edge detection; Image segmentation; Liver; Measurement; Noise; Ultrasonic imaging; Active contour model; Difference of offset Gaussian; Hemangioma; Image processing; Liver; Ultrasound; Algorithms; Automation; Hemangioma; Humans; Image Processing, Computer-Assisted; Liver Neoplasms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2011.6091970
Filename :
6091970
Link To Document :
بازگشت