title: Noise equalization for detection of microcalcification clusters in direct digital mammogram images.
abstract: Equalizing image noise is shown to be an important step in the automatic detection of microcalcifications in digital mammography. This study extends a well established film-screen noise equalization scheme developed by Veldkamp et al. for application to full-field digital mammogram (FFDM) images. A simple noise model is determined based on the assumption that quantum noise is dominant in direct digital X-ray imaging. Estimation of the noise as a function of the gray level is improved by calculating the noise statistics using a truncated distribution method. Experimental support for the quantum noise assumption is presented for a set of step wedge phantom images. Performance of the noise equalization technique is also tested as a preprocessing stage to a microcalcification detection scheme. It is shown that the square root model based approach which FFDM allows leads to a robust estimation of the high frequency image noise. This provides better microcalcification detection performance when compared to the film-screen noise equalization method developed by Veldkamp. Substantially better results are obtained than when noise equalization is omitted. A database of 124 direct digital mammogram images containing 28 microcalcification clusters was used for evaluation of the method.
authors.affiliation: University of Canterbury, Department of Electrical and Computer Engineering, Christchurch, New Zealand.
authors.forename: Kristin J
authors.initials: KJ
authors.lastname: McLoughlin
authors.forename: Philip J
authors.initials: PJ
authors.lastname: Bones
authors.forename: Nico
authors.initials: N
authors.lastname: Karssemeijer
mesh_terms: D000465:Algorithms; D001941:Breast Diseases / Q000000981:diagnostic imaging* / Q000473:pathology; D002114:Calcinosis / Q000000981:diagnostic imaging* / Q000473:pathology; D016000:Cluster Analysis; D006801:Humans; D008327:Mammography / Q000295:instrumentation / Q000379:methods*; D010363:Pattern Recognition, Automated; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000295:instrumentation / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013269:Stochastic Processes