a Path for Segmentation Through Sequential Learning
and , where is a neighborhood surrounding x and is the image features extracted from the neighborhood. Given the estimated probabilities, the maximum a posterior (MAP) segmentation can be derived…
and , where is a neighborhood surrounding x and is the image features extracted from the neighborhood. Given the estimated probabilities, the maximum a posterior (MAP) segmentation can be derived…
(1) where is the signal for the dPFG sequence with parallel gradients, is the signal for the dPFG sequence with perpendicular gradients, is the wavenumber, the gyromagnetic ratio, G the…
Fig. 1. (left) Brain images of MS patients with (right) lesions segmented by experts. We show (a) a volume with heavy peri-ventricular lesion load, (b) volume with supra-ventricular lesions, and…
where X is an m-by-n (n$$” src=”/wp-content/uploads/2016/09/A339424_1_En_10_Chapter_IEq8.gif”> so that it is possible to estimate . The maximum-likelihood and unbiased estimate of is The residuals and the unbiased estimate of are…
vertices, and assume all surfaces to be registered to the same reference [9]. As a result, all surface vertices have direct correspondence across all subjects. Furthermore, we consider that a…
Fig. 1. Definition of body sections. Human body is divided into 12 continuous parts. Each parts may cover different ranges due to the variability of anatomies (Color figure online). In…
Fig. 1. Laparoscopic images of the uterus. FU-junctions are shown in blue and green for left and right respectively. The detection difficulty comes from ligament junctions, variation in the Fallopian…
Fig. 1. Illustration of keypoint transfer segmentation. First, keypoints (white circles) in training and test images are matched (arrow). Second, voting assigns an organ label to the test keypoint (r.Kidney)….
between two points i and j in the image domain, defined by (1)where is the spatial Euclidean distance, is the image intensity similarity, and these two different measures are combined…
consists of N voxels observed at T time points. The functional architecture of a brain state can be modeled as a connectivity graph G with vertices V representing the voxels,…