Classification of breast ultrasound images using fractal feature
學年 93
學期 2
出版(發表)日期 2005-07-01
作品名稱 Classification of breast ultrasound images using fractal feature
著者 Dar-Ren Chen; Ruey-Feng Chang; Chii-Jen Chen; Ming-Feng Ho; Shou-Jen Kuo; Shou-Tung Chen; Shin-Jer Hung; Woo Kyung Moon
著錄名稱、卷期、頁數 Clinical Imaging 29(4), p.235-245
摘要 Fractal analyses have been applied successfully for the image compression, texture analysis, and texture image segmentation. The fractal dimension could be used to quantify the texture information. In this study, the differences of gray value of neighboring pixels are used to estimate the fractal dimension of an ultrasound image of breast lesion by using the fractal Brownian motion. Furthermore, a computer-aided diagnosis (CAD) system based on the fractal analysis is proposed to classify the breast lesions into two classes: benign and malignant. To improve the classification performances, the ultrasound images are preprocessed by using morphology operations and histogram equalization. Finally, the k-means classification method is used to classify benign tumors from malignant ones. The US breast image databases include only histologically confirmed cases: 110 malignant and 140 benign tumors, which were recorded. All the digital images were obtained prior to biopsy using by an ATL HDI 3000 system. The receiver operator characteristic (ROC) area index AZ is 0.9218, which represents the diagnostic performance.
關鍵字 Fractal;Texture;Ultrasound;Box counting;Brownian motion;Fractal dimension;k-means classification
語言 en_US
ISSN 1873-4499;0899-7071
期刊性質 國外
收錄於 SCI
國別 USA
出版型式 ,電子版,紙本

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