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

fYear

2010

fDate

Aug. 31 2010-Sept. 4 2010

Firstpage

4752

Lastpage

4755

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE

Conference_Location

Buenos Aires

ISSN

1557-170X

Print_ISBN

978-1-4244-4123-5

Type

conf

DOI

10.1109/IEMBS.2010.5626376

Filename

5626376