Title :
Soft thresholding for medical image segmentation
Author :
Aja-Fernández, Santiago ; Vegas-Sánchez-Ferrero, Gonzalo ; Fernández, Miguel A Martín
Author_Institution :
LPI, Univ. de Valladolid, Valladolid, Spain
fDate :
Aug. 31 2010-Sept. 4 2010
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.
Keywords :
fuzzy logic; image segmentation; medical image processing; image histogram; medical image segmentation; membership function; soft thresholding; spatial processing; Biomedical imaging; Fuzzy sets; Histograms; Image segmentation; Noise measurement; Pixel; Ultrasonic imaging; Algorithms; Artificial Intelligence; Brain; Image Enhancement; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
Print_ISBN :
978-1-4244-4123-5
DOI :
10.1109/IEMBS.2010.5626376