In this paper we describe a novel pixel-based strategy of segmentation and stereovision
matching for obtaining disparity maps from hemispherical images captured with fish-eye lenses …

… using fuzzy logic. MRI intensity inhomogeneities can be attributed to imperfections in the
radio-… by modifying the objective function of the standard fuzzy c-means (FCM) algorithm to …

… In general, the fuzzy C-means approach (FCM) is highly effective for image segmentation. It
… The bias can result from several causes, with inhomogeneities in the radio frequency field or …

… many segmentation algorithms … segmentation accuracy for image details. To further improve
the accuracy for brain MR image segmentation, a robust spatially constrained fuzzy c-means …

… In this paper, we present a fuzzy c-means (FCM) algorithm that incorporates spatial information
… This technique is a powerful method for noisy image segmentation and works for both …

… of Fuzzy C-means (FCM) and k-Means segmentation, with histogram guided initialization,
on tumor edema complex MR images. The accuracy of any segmentation … the segmentation …

… inhomogeneity induced by the radio-frequency coil in MR … fuzzy C-means (KFCM) algorithm
is proposed to compensate for such a lack and then applied to the MR image segmentation. …

… shift based fuzzy c-means algorithm that requires less computational time than previous
techniques while providing good segmentation results. The proposed segmentation method …

… Spatial intensity inhomogeneity induced by the radio … fuzzy c-means (MFCM) algorithm for
adaptive segmentation … objective function of the standard fuzzy c-means (FCM) algorithm to …

… In this paper we would like to propose an extension to the popular fuzzy c-means clustering
method by introducing an additional disparity cue. The reason for introducing the additional …