Performance analysis of bias correction techniques in brain MR images

Abstract

Bias field is a smooth intensity variation, which emanate during the process of image procurement. Bias removal is an essential prerequisite while incorporating computer assisted diagnosis. Several bias correction algorithms are proposed till date. This paper scrutinizes the prominent bias correction algorithms, LEMS, MICO, BCFCM and N3. These investigations carried over the substantial amount of T1 and T2 weighted brain MR images with different bias spectrum from Brain Web website. Algorithms efficiency are analyzed in spectral wise, slice wise, and type wise. Based upon the performance indicators coefficient of variation and coefficient of joint variation, the algorithms are assessed and ranked. The result concludes that which algorithm exterminates the bias field, presents in brain MR images in an efficient manner.