Segmentation of solid nodules in ultrasonographic breast image based on wavelet transform.
An accurate segmentation of solid nodules in ultrasonographic (US) breast image is presented. 1-level 2-dimensional Discrete Wavelet Transform (DWT) is used to create features reflecting the texture information of the original image. Using these features, the texture classification is achieved. Finally, solid nodule region is segmented from the classified texture region. Proper threshold for texture classification is automatically decided. Empirically acquired information about the relationship between the texture characteristic of the original image and the optimal threshold is examined and used. Presented algorithm is applied to 284 malignant solid nodules and 300 benign solid nodules and the resulting images are presented.
Park
Sangyun
S
Interdisciplinary Program, Biomedical Engineering Major, Graduate School, Seoul National University, Seoul, Korea. pinkydays@melab.snu.ac.kr
Kong
Hyoun-Joong
HJ
Moon
Woo Kyoung
WK
Kim
Hee Chan
HC
D000465:Algorithms; D001185:Artificial Intelligence; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D016217:Ultrasonography, Mammary / Q000379:methods*