Fuzzy logic and local features based medical image segmentation

Author

Javed, U. ; Riaz, M.M. ; Khokher, Muhammad Rizwan ; Ghafoor, Abdul ; Cheema, T.A.

Author_Institution

Fac. of Eng. & Technol., Int. Islamic Univ., Islamabad, Pakistan

fYear

2013

fDate

15-18 Sept. 2013

Firstpage

1148

Lastpage

1152

Abstract

A fuzzy logic based active contour model for medical image segmentation is proposed. Image local features are incorporated in active contour model. Fuzzy logic is used to assign weights to pixels. Higher weights are assigned to pixels having less entropy and local variance whereas Lower weights are assigned to pixels having high entropy and local variance. Simulation results show the improvement in segmentation results in terms of efficiency and accuracy.

Keywords

feature extraction; fuzzy logic; image segmentation; inference mechanisms; medical image processing; active contour model; entropy; fuzzy logic; image local features; local features based medical image segmentation; pixel weights; segmentation accuracy; segmentation efficiency; variance; Active contours; Biomedical imaging; Entropy; Fuzzy logic; Image segmentation; Level set; Solid modeling; Active Contours; Fuzzy Logic; Image features; Image segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing (ICIP), 2013 20th IEEE International Conference on

Conference_Location

Melbourne, VIC

Type

conf

DOI

10.1109/ICIP.2013.6738237

Filename

6738237

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3273987