title: Soft thresholding for medical image segmentation.
abstract: A new soft thresholding method is presented. The method is based on relating each pixel in the image to the different regions via a membership function, rather than through hard decisions. The membership function of each of the regions is derived from the histogram of the image. As a consequence, each pixel will belong to different regions with a different level of membership. This feature is exploited through spatial processing to make the thresholding robust to noisy environments.
authors.affiliation: LPI, ETSI Telecomunicación, Universidad de Valladolid (Spain). sanaja@tel.uva.es
authors.forename: Santiago
authors.initials: S
authors.lastname: Aja-Fernandez
authors.forename: Gonzalo
authors.initials: G
authors.lastname: Vegas-Sanchez-Ferrero
authors.forename: Miguel A
authors.initials: MA
authors.lastname: Martin Fernandez
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000033:anatomy & histology*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity