title: Computerized-aid diagnosis of breast mass using ultrasound image.
abstract: This paper presents a comparative study of the diagnostic results of the ultrasologists with/without using a novel enhancement algorithm for breast ultrasonic images based on fuzzy entropy principle and textural information. Totally, 350 ultrasound images of 115 cases were analyzed including 59 benign and 56 malignant lesions. The original breast images were fuzzified, the edge and textural information were extracted, and the images were enhanced. The original and enhanced images were assessed and evaluated by ultrasologists using double blind method before and after enhancement. The diagnostic sensitivity and specificity were calculated by the areas (Az) under the receiver operating characteristic (ROC) curves. And the two diagnostic results before and after enhancement were compared by Chi-square test in a 2 x 2 table. The results demonstrated that the discrimination rate of breast masses had been highly improved after employing the novel enhancement algorithm. The result indicates the sensitivity could be raised from 74.3% to 89.3% with the false-positive rate 14.3%, and the area (Az) under the ROC curve of diagnosis also increased from 0.84 to 0.93. The novel enhancement algorithm can increase the classification accuracy and decrease the rate of missing and misdiagnosis, and it is useful for breast cancer control.
authors: Department of Ultrasound, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, People's Republic of China.
authors: Jia-Wei
authors: JW
authors: Tian
authors: Li-Tao
authors: LT
authors: Sun
authors: Yan-Hui
authors: YH
authors: Guo
authors: H D
authors: HD
authors: Cheng
authors: Ying-Tao
authors: YT
authors: Zhang
mesh_terms: D000328:Adult; D000465:Algorithms; D001940:Breast / Q000473:pathology; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging* / Q000401:mortality / Q000473:pathology*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D017143:Fuzzy Logic; D006801:Humans; D007091:Image Processing, Computer-Assisted; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D012372:ROC Curve; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016217:Ultrasonography, Mammary / Q000295:instrumentation / Q000379:methods*