DocumentCode :
853488
Title :
Characterization of spiculation on ultrasound lesions
Author :
Huang, Sheng-Fang ; Chang, Ruey-Feng ; Chen, Dar-Ren ; Moon, Woo Kyung
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Chung Cheng Univ., Taiwan, Taiwan
Volume :
23
Issue :
1
fYear :
2004
Firstpage :
111
Lastpage :
121
Abstract :
Spiculation is a stellate distortion caused by the intrusion of breast cancer into surrounding tissue. Its existence is an important clue to characterizing malignant tumors. Many successful mammographic methods have been proposed to detect tumors with spiculation. Traditional two-dimensional (2-D) ultrasound cannot easily find spiculations because spiculations normally appear parallel to the surface of the skin. Recently, three-dimensional (3-D) ultrasound has been gradually used in clinical applications and it has been proven to be useful in determining the architectural distortion or spiculation that surrounds a breast tumor. This paper aims to identify spiculation from 3-D ultrasonic volume data of a tumor found by a physician. In the proposed method, each coronal slice of volume data is successively extracted and then analyzed as a 2-D ultrasound image by the proposed spiculation detection method. First, in each horizontal slice, the modified rotating structuring element (ROSE) operation is used to find the central region in which spiculation lines converge. Second, the stick algorithm is used to estimate the direction of the edge of each pixel around the central region. A pixel whose edge points toward the central region is marked as a potential spiculation. Finally, the marked pixels are collected around the central region and their distribution is analyzed to determine whether spiculation is present. The 3-D test datasets were obtained using the Voluson 530 or 730, Kretztechnik, Austria. First, the proposed method was tested on 104 2-D typical coronal images (selected by an experienced physician) extracted from 52 3-D ultrasonic datasets. Finally, 225 3-D pathologically proven datasets were tested to evaluate the performance. Spiculations are more easily observed in the coronal view than in the other two views. That is, the 3-D ultrasound is a powerful tool for identifying spiculations. Furthermore, 16% (19/120) of benign cases and 90% (94/105) of malignant c- - ases are detected as spiculations.
Keywords :
biomedical ultrasonics; cancer; feature extraction; mammography; medical image processing; tumours; Austria; Kretztechnik; Voluson 530; Voluson 730; breast cancer intrusion; coronal slice; malignant tumors; mammographic methods; modified rotating structuring element operation; spiculation; stellate distortion; stick algorithm; tissue; ultrasound lesions; Breast cancer; Breast neoplasms; Breast tumors; Data mining; Lesions; Malignant tumors; Skin; Testing; Two dimensional displays; Ultrasonic imaging; Algorithms; Breast Neoplasms; Female; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Reproducibility of Results; Sensitivity and Specificity; Ultrasonography, Mammary;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2003.819918
Filename :
1256432
Link To Document :
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