title: Support vector machine classification based on correlation prototypes applied to bone age assessment.
abstract: Bone age assessment (BAA) on hand radiographs is a frequent and time consuming task in radiology. We present a method for (semi)automatic BAA which is done in several steps: (i) extract 14 epiphyseal regions from the radiographs, (ii) for each region, retain image features using the IRMA framework, (iii) use these features to build a classifier model (training phase), (iv) evaluate performance on cross validation schemes (testing phase), (v) classify unknown hand images (application phase). In this paper, we combine a support vector machine (SVM) with cross-correlation to a prototype image for each class. These prototypes are obtained choosing one random hand per class. A systematic evaluation is presented comparing nominal- and real-valued SVM with k nearest neighbor (kNN) classification on 1,097 hand radiographs of 30 diagnostic classes (0 19 years). Mean error in age prediction is 1.0 and 0.83 years for 5-NN and SVM, respectively. Accuracy of nominal- and real-valued SVM based on 6 prominent regions (prototypes) is 91.57% and 96.16%, respectively, for accepting about two years age range.
authors.forename: M
authors.initials: M
authors.lastname: Harmsen
authors.forename: B
authors.initials: B
authors.lastname: Fischer
authors.forename: H
authors.initials: H
authors.lastname: Schramm
authors.forename: T
authors.initials: T
authors.lastname: Seidl
authors.forename: T M
authors.initials: TM
authors.lastname: Deserno
mesh_terms: D000293:Adolescent; D000328:Adult; D000365:Age Determination by Skeleton / Q000379:methods*; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D005260:Female; D050276:Hand Bones / Q000033:anatomy & histology* / Q000000981:diagnostic imaging; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D060388:Support Vector Machine; D055815:Young Adult