Managing nature of images induced by noise with the fusion of fuzzy algorithms has been a challenge. Traditional Fuzzy C Means (FCM) calculation is amazingly noise sensitive and fails in giving great results. Subsequently, as an answer for this issue Tripathy et. al presented a change of fuzzy c means which includes calculation that consolidated spatial data and intuition. The spatial capacity is the summation of the considerable number of estimations of the participation elements of the pixel's neighborhood which is under consideration. This methodology ended up being a right answer for the noise affectability issues when contrasted with FCM. This calculation incorporates an intuitionistic component in the enrollment capacity of the current spatial FCM (sFCM). Intuitionism manages the wavering segment that emerges because of less data and insufficient learning. This is superior to anything existing calculations. This spatial IFCM(sIFCM) has been connected on leukaemia images. © 2016, Institute of Integrative Omics and Applied Biotechnology. All rights reserved.