title: Computer-aided diagnosis of sonographic liver cirrhosis: a spleen-reference approach.
abstract: This article aimed to develop a computer-aided diagnosis (CAD) algorithm for differential diagnosis of cirrhotic and noncirrhotic livers, allowing free adjustment of system settings to obtain the best scanned images. A spleen-referenced approached was proposed. 505 pairs of images acquired from 322 subjects using three ultrasound imaging systems were evaluated. Each pair consisted of liver and spleen sonograms of the same subject. Medical doctors were free to adjust the system parameters to attain the best scanned images. Of these 322 subjects, 155 subjects were cirrhotic, and 167 subjects noncirrhotic. Four assessments were carried out to evaluate the effectiveness and robustness of the proposed algorithm on the variations of regions-of-interest, ultrasound imaging systems, and scanned images. Four feature pairs were proposed. A logistic regression function was used as the classifier. All performances were evaluated by the leave-one-out cross-validation method. The proposed algorithm was compared with two previous CAD algorithms and all performance comparisons were based on paired-sample t tests. The mean A(z) values of the receiver operating characteristic curves and classification accuracies ranged as high as from 0.949 to 0.996 and from 91.58% to 97.30%, respectively, for the four assessments. At the 5% family-wise significance level, the proposed algorithm was shown to be superior to the two previous CAD algorithms and their modified versions in terms of the A(z) values.
authors.affiliation: Department of Internal Medicine, College of Medicine, National Taiwan University, Division of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.
authors.forename: Pei-Ming
authors.initials: PM
authors.lastname: Yang
authors.forename: Chung-Ming
authors.initials: CM
authors.lastname: Chen
authors.forename: Tung-Wu
authors.initials: TW
authors.lastname: Lu
authors.forename: Chih-Pin
authors.initials: CP
authors.lastname: Yen
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001185:Artificial Intelligence; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008103:Liver Cirrhosis / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D012016:Reference Values; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013154:Spleen / Q000000981:diagnostic imaging*; D013382:Subtraction Technique; D014463:Ultrasonography / Q000379:methods*