title: Speckle reduction approach for breast ultrasound image and its application to breast cancer diagnosis.
abstract: OBJECTIVE
  To retrospectively evaluate the effects of a speckle reduction algorithm on radiologists' diagnosis of malignant and benign breast lesions on ultrasound (US) images.
  
  
  METHODS
  Using a database of 603 breast (US) images of 211 cases (109 benign lesions and 102 malignant ones), the original and speckle-reduced images were assessed by five radiologists and final assessment categories were assigned to indicate the probability of malignancy according to BI-RADS-US. The diagnostic sensitivity and specificity were investigated by the areas (Az) under the receiver operating characteristic (ROC) curves.
  
  
  RESULTS
  The sensitivity and specificity of breast lesions on Ultrasound images improved from 88.7% to 94.3%, from 68.6% to 75.2%, respectively, and the area (Az) under ROC curve of diagnosis also increased from 0.843 to 0.939, Z=4.969, there were significant differences in the Az between the original breast lesions and speckle-reduced ones on Ultrasound images (P<0.001). The diagnostic accuracy of breast lesions had been highly improved from 78.67% to 92.73% after employing this algorithm.
  
  
  CONCLUSIONS
  The results demonstrate the promising performance of the proposed speckle reduction algorithm in distinguishing malignant from benign breast lesions which will be useful for breast cancer diagnosis.
authors.affiliation: Ultrasound Department, The Second Affiliated Hospital, Key Laboratory of Education Ministry for Myocardial Ischemia Mechanism and Treatment, Harbin Medical University, 148 Baojian Road, Harbin 150086, Heilongjiang, China.
authors.forename: Yanxin
authors.initials: Y
authors.lastname: Su
authors.forename: Hong
authors.initials: H
authors.lastname: Wang
authors.forename: Ying
authors.initials: Y
authors.lastname: Wang
authors.forename: Yanhui
authors.initials: Y
authors.lastname: Guo
authors.forename: Hengda
authors.initials: H
authors.lastname: Cheng
authors.forename: Yingtao
authors.initials: Y
authors.lastname: Zhang
authors.forename: Jiawei
authors.initials: J
authors.lastname: Tian
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D016477:Artifacts; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008875:Middle Aged; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016217:Ultrasonography, Mammary / Q000379:methods*; D055815:Young Adult